路基强度的快速无损检测、评价与控制研究
|
摘要
路基是路面结构的支撑体,在实践中常常出现的路面损坏现象大部分都是由于路基强度不足,稳定性变差,在外荷载作用下产生过量变形所致。路基的施工质量是获得坚实而又稳定的路基和保证路基路面整体具有良好使用性能的关键。如何快速可靠地进行路基施工质量的评价、有效地进行路基施工过程的质量控制和及时消除路基施工的质量隐患,是确保高等级公路路基路面质量和使用寿命的关键技术之一。本文对路基强度的快速无损检测、评价与控制技术进行了如下研究：
1、首先分析了FWD与PFWD的工作特性,以及FWD和PFWD的性能指标、测试过程和检测结果,采用有限元软件对便携式落锤弯沉仪的测试过程进行了动态仿真,分析在不同承载板直径、不同锤重、以及不同测试土体对测试结果的影响,并在此基础上结合承载板试验的控制标准提出了不同填料路基的PFWD测试的推荐配置。
2、提出了自适应信息遗传算法,针对于模量反算中,目标函数在最优值附近表现为大片狭长平坦区域的特点,提出了一类模量反算新算法——自适应信息遗传算法,首次提出了根据信息量大小来确定算法是否进行自适应细分模量解空间的机制,缩小算法后期反算中的搜索空间,此外,新算法中还改进了实数交叉算子,使用了新的探险策略。从而加强了新算法后期的局部搜索能力。这新机制、新策略的引入大大提高了模量反算的求解效率,降低了算法复杂度。本算法无论在反算结果精度还是速度方面,都得到了极大改进,能够满足工程实际中进行大量模量反算的要求。
3、建立了路基施工质量均匀性评价方法中涉及的数学模型,并将广泛应用的曲面拟合方法引入路基评价领域,利用已测数据拟合出真实模量曲面。其次,进一步在该拟合曲面的基础上,提出了本文的均匀性评价方法---伪方差-均值综合评价法。随后的模拟验证表明,该方法能对路基施工质量的实际状况进行有效评价。
4、根据公路可靠度设计的基本原理,研究了路基回弹模量变异系数对路面可靠度的影响,确定了采用可靠度对路基均匀性进行分析的原理及方法,并提出了以路基回弹模量变异系数作为路基均匀性评价指标；以《公路工程结构可靠度设计统一标准》(GB/T50283-1999)中规定的公路路面目标可靠度为基础,制订了评价路基均匀性的可靠度划分依据,将各级公路路基均匀性等级分为优、中、差三个级别；通过建立有限元模型分别对沥青路面结构、水泥混凝土路面结构在不同路基回弹模量、不同变异系数条件下的结构可靠度进行分析计算,得出了划分路基均匀性等级的回弹模量变异系数临界值,制定了基于可靠度的路基均匀性评价标准。
5、针对我国现行规范中路基设计参数与施工质量检测指标不统一的问题,通过对12条公路32个路段成型路基的现场调查和检测,得到了现场承载板法实测路基回弹模量Eb、贝克曼梁实测弯沉l、PFWD实测路基模量Ep及灌砂法实测压实度K、含水率w和稠度wc等检测结果,以现场承载板法实测的路基回弹模量为准,建立了路基回弹模量和弯沉的综合经验关系,以及路基回弹模量与施工指标之间的关系,将路基设计参数回弹模量与施工控制指标压实度有机地联系起来,从而确定回弹模量的合理取值标准,为路面结构设计以及路基施工质量控制提供合理的参考依据。
Subgrade is the support of pavement structure. In practice, the usual damage phenomenon of the pavement are due to the lack of subgrade strength, deteriorated stability and excessive deformation due to external loads in most cases. The strength and stablility of subgrade and the service performance of subgrade and pavement as a whole are based on the quality of construction of subgrade. One key technology to ensure service property of the road and service life of high-grade highway is how to quickly and reliably evaluate the quality of subgrade construction, effectively control the quality of construction process and timely eliminate the quality bugs of subgrade construction in our province and even the country. In this paper, rapid non-destructive testing, evaluation and control techniques of subgrade strength are studied as the following:
1. The characteristics of rapid non-destructive testing equipment FWD (falling weight deflectometer) and PFWD(portable falling weight deflectometer) applied in the detection of subgrade strength are introduced in detail. We analysed performance indicators, tested procedures and test results of FWD and PFWD, and presented technical points that worth our notice and technical superiority of FWD instrument in the course, then we proposed two ways to assess the bearing capacity of pavement structure and their respective scope to adapt. Whether PFWD is reliable to test subgrade resilient modulus is analysed, and the result shows that PFWD can be used to test subgrade resilient modulus.
2. Adaptive information Genetic Algorithm is proposed. In anti-calculation of the modulus, for the objective function shows as a long, narrow and large flat area when it is in the vicinity of the optimal value, a new kind of anti-calculation on the modulus——adaptive information Genetic Algorithm is put forward. The mechanism that whether we should take self-adaptive segmentation algorithm modulus which is depended upon the size of the information so that the latter part of anti-calculation algorithm in the search space could be reduced is proposed for the first time. In addition, the new algorithm also improves the real crossover operator by using a new exploration strategy. Thereby, it strengthens the local search capabilities in the latter part of the new algorithm. The introduction of this new mechanism and the new strategy makes solving efficiency of anti-calculation on the modulus much faster and reduces the algorithm complexity. The algorithm improves the anti-calculation accuracy and the speed so that it could meet the requirements of anti-calculation on the modulus in the engineering practice.
3. The research of the method to evaluate uniformity of subgrade construction quality is conducted. Firstly the mathematical model involved in evaluation is established, and surface fitting method which has been widely used in statistics into the field of evaluation of subgrade is introduced for the first time. With measured data, we can fit out the real modulus surface. Further more, based on the fitted-out surface, uniformity evaluation method——pseudo-variance mean value comprehensive evaluation method is proposed. The subsequent simulation trials showed that the method could effectively evaluate the actual situation of subgrade construction quality.
4. According to the basic principles of Reliability-based Design of Highway, the impact on the reliability of pavement that comes from the subgrade resilient modulus coefficient of variation is studied, and the theory and methods to analyse subgrade uniformity based on the reliability of pavement were determined. Also, the method that subgrade resilient modulus coefficient of variation can be taken as an evaluation index of subgrade uniformity was proposed. Based on the specified target reliability of pavement in" Unified Standard for Reliability-based Design of Highway Engineering Structural"(GB/T50283-1999), division evidence of reliability used in evaluation of subgrade uniformity was established, and then classification of subgrade uniformity is divided into superior, middle, and poor. Through the creation of finite element model, structural reliability of asphalt pavement structure and the structure of cement concrete pavement was analysed and calculated under different subgrade resilient modulus, different coefficient of variation respectively, and the critical value of coefficient of variation of subgrade resilient modulus to classify subgrade uniformity was got, and then evaluation criteria of subgrade uniformity based on reliability was established.
5. About the difference between subgrade design parameters and detection index of construction quality in China's current specifications, through on-site investigations and tests of formed subgrade that were conducted in32sections of12highways, the test results of subgrade resilient modulus E b with on-site bearing plate method, Beckman Beam beam deflection value1, subgrade modulus E p measured by PFWD, practical compactness K with sand replacement method, water content w, consistency w c and so on were got. Based on the standard of the subgrade resilient modulus E b with on-site bearing plate method, comprehensive experience relationship between subgradeo resilient modulus and deflection were determined and the relationship between subgrade resilient modulus and construction indicators. The relationship between the design parameters of the subgrade resilient modulus and compactness used as construction control was establisher organically, so reasonable values of resilient modulus which provide reasonable reference for pavement design and subgrade construction quality control could be determined.
1、首先分析了FWD与PFWD的工作特性,以及FWD和PFWD的性能指标、测试过程和检测结果,采用有限元软件对便携式落锤弯沉仪的测试过程进行了动态仿真,分析在不同承载板直径、不同锤重、以及不同测试土体对测试结果的影响,并在此基础上结合承载板试验的控制标准提出了不同填料路基的PFWD测试的推荐配置。
2、提出了自适应信息遗传算法,针对于模量反算中,目标函数在最优值附近表现为大片狭长平坦区域的特点,提出了一类模量反算新算法——自适应信息遗传算法,首次提出了根据信息量大小来确定算法是否进行自适应细分模量解空间的机制,缩小算法后期反算中的搜索空间,此外,新算法中还改进了实数交叉算子,使用了新的探险策略。从而加强了新算法后期的局部搜索能力。这新机制、新策略的引入大大提高了模量反算的求解效率,降低了算法复杂度。本算法无论在反算结果精度还是速度方面,都得到了极大改进,能够满足工程实际中进行大量模量反算的要求。
3、建立了路基施工质量均匀性评价方法中涉及的数学模型,并将广泛应用的曲面拟合方法引入路基评价领域,利用已测数据拟合出真实模量曲面。其次,进一步在该拟合曲面的基础上,提出了本文的均匀性评价方法---伪方差-均值综合评价法。随后的模拟验证表明,该方法能对路基施工质量的实际状况进行有效评价。
4、根据公路可靠度设计的基本原理,研究了路基回弹模量变异系数对路面可靠度的影响,确定了采用可靠度对路基均匀性进行分析的原理及方法,并提出了以路基回弹模量变异系数作为路基均匀性评价指标；以《公路工程结构可靠度设计统一标准》(GB/T50283-1999)中规定的公路路面目标可靠度为基础,制订了评价路基均匀性的可靠度划分依据,将各级公路路基均匀性等级分为优、中、差三个级别；通过建立有限元模型分别对沥青路面结构、水泥混凝土路面结构在不同路基回弹模量、不同变异系数条件下的结构可靠度进行分析计算,得出了划分路基均匀性等级的回弹模量变异系数临界值,制定了基于可靠度的路基均匀性评价标准。
5、针对我国现行规范中路基设计参数与施工质量检测指标不统一的问题,通过对12条公路32个路段成型路基的现场调查和检测,得到了现场承载板法实测路基回弹模量Eb、贝克曼梁实测弯沉l、PFWD实测路基模量Ep及灌砂法实测压实度K、含水率w和稠度wc等检测结果,以现场承载板法实测的路基回弹模量为准,建立了路基回弹模量和弯沉的综合经验关系,以及路基回弹模量与施工指标之间的关系,将路基设计参数回弹模量与施工控制指标压实度有机地联系起来,从而确定回弹模量的合理取值标准,为路面结构设计以及路基施工质量控制提供合理的参考依据。
Subgrade is the support of pavement structure. In practice, the usual damage phenomenon of the pavement are due to the lack of subgrade strength, deteriorated stability and excessive deformation due to external loads in most cases. The strength and stablility of subgrade and the service performance of subgrade and pavement as a whole are based on the quality of construction of subgrade. One key technology to ensure service property of the road and service life of high-grade highway is how to quickly and reliably evaluate the quality of subgrade construction, effectively control the quality of construction process and timely eliminate the quality bugs of subgrade construction in our province and even the country. In this paper, rapid non-destructive testing, evaluation and control techniques of subgrade strength are studied as the following:
1. The characteristics of rapid non-destructive testing equipment FWD (falling weight deflectometer) and PFWD(portable falling weight deflectometer) applied in the detection of subgrade strength are introduced in detail. We analysed performance indicators, tested procedures and test results of FWD and PFWD, and presented technical points that worth our notice and technical superiority of FWD instrument in the course, then we proposed two ways to assess the bearing capacity of pavement structure and their respective scope to adapt. Whether PFWD is reliable to test subgrade resilient modulus is analysed, and the result shows that PFWD can be used to test subgrade resilient modulus.
2. Adaptive information Genetic Algorithm is proposed. In anti-calculation of the modulus, for the objective function shows as a long, narrow and large flat area when it is in the vicinity of the optimal value, a new kind of anti-calculation on the modulus——adaptive information Genetic Algorithm is put forward. The mechanism that whether we should take self-adaptive segmentation algorithm modulus which is depended upon the size of the information so that the latter part of anti-calculation algorithm in the search space could be reduced is proposed for the first time. In addition, the new algorithm also improves the real crossover operator by using a new exploration strategy. Thereby, it strengthens the local search capabilities in the latter part of the new algorithm. The introduction of this new mechanism and the new strategy makes solving efficiency of anti-calculation on the modulus much faster and reduces the algorithm complexity. The algorithm improves the anti-calculation accuracy and the speed so that it could meet the requirements of anti-calculation on the modulus in the engineering practice.
3. The research of the method to evaluate uniformity of subgrade construction quality is conducted. Firstly the mathematical model involved in evaluation is established, and surface fitting method which has been widely used in statistics into the field of evaluation of subgrade is introduced for the first time. With measured data, we can fit out the real modulus surface. Further more, based on the fitted-out surface, uniformity evaluation method——pseudo-variance mean value comprehensive evaluation method is proposed. The subsequent simulation trials showed that the method could effectively evaluate the actual situation of subgrade construction quality.
4. According to the basic principles of Reliability-based Design of Highway, the impact on the reliability of pavement that comes from the subgrade resilient modulus coefficient of variation is studied, and the theory and methods to analyse subgrade uniformity based on the reliability of pavement were determined. Also, the method that subgrade resilient modulus coefficient of variation can be taken as an evaluation index of subgrade uniformity was proposed. Based on the specified target reliability of pavement in" Unified Standard for Reliability-based Design of Highway Engineering Structural"(GB/T50283-1999), division evidence of reliability used in evaluation of subgrade uniformity was established, and then classification of subgrade uniformity is divided into superior, middle, and poor. Through the creation of finite element model, structural reliability of asphalt pavement structure and the structure of cement concrete pavement was analysed and calculated under different subgrade resilient modulus, different coefficient of variation respectively, and the critical value of coefficient of variation of subgrade resilient modulus to classify subgrade uniformity was got, and then evaluation criteria of subgrade uniformity based on reliability was established.
5. About the difference between subgrade design parameters and detection index of construction quality in China's current specifications, through on-site investigations and tests of formed subgrade that were conducted in32sections of12highways, the test results of subgrade resilient modulus E b with on-site bearing plate method, Beckman Beam beam deflection value1, subgrade modulus E p measured by PFWD, practical compactness K with sand replacement method, water content w, consistency w c and so on were got. Based on the standard of the subgrade resilient modulus E b with on-site bearing plate method, comprehensive experience relationship between subgradeo resilient modulus and deflection were determined and the relationship between subgrade resilient modulus and construction indicators. The relationship between the design parameters of the subgrade resilient modulus and compactness used as construction control was establisher organically, so reasonable values of resilient modulus which provide reasonable reference for pavement design and subgrade construction quality control could be determined.
引文
[1]王俊梅.土基回弹模量及其测试方法研究[D].西安：长安大学,2004.
[2]杨永红.甘肃黄土地区土基回弹模量[J].长安大学学报(自然科学版),2005,25(3)：7-10.
[3]叶燕呼.广东省公路路基土强度及其分级研究[J].公路,2000,3：14-20.
[4]吴德华.陕西关中地区土基回弹模量研究[J].公路交通科技,2005,22(2)：27-30.
[5]沈金安.国外沥青路面设计方法总汇[M].北京：人民交通出版社,2004.
[6]邓露.路基土的CBR强度与压实度关系的试验研究[J].华中科技大学学报,2005,22(增刊)：109-115.
[7]陈晓光.新疆高等级公路半刚性基层土基强度等级划分[J].公路交通科技,1999,16(3)：13-16.
[8]李喜安.公路黄土路基动力学参数的影响因素及其规律研究[J].公路交通科技,2005,22(6)：87-91.
[9]杨广庆.细粒土路基的弹性模量[J].路基工程,2000,91(4)：42-44.
[10]卢永贵.成都粘土及其石灰稳定土的动力特性试验研究[J].路基工程,1998,77(2)：34-37.
[11]张洪华.应用FWD测定土基回弹模量的研究[J].中国公路学报,1994,17(增1期)：9-13.
[12]George K P. Subgrade Characterization Employing the Falling Weight Deflectometer[A]. TRB.82th Annual Meeting,2003
[13]Chai G. The Structural Response and Behavior Prediction of Subgrade Soils Using Falling Weight Deflectometer in Pavement Construction [A]. Proceedings,Third International Conference on Road & Airfield Pavement Technology, Beijing, China,1998.
[14]王端宜.手持式落锤式弯沉仪用于路基强度评价的尝试[J].公路,2002,9：108-110.
[15]Livneh M. Use of Falling Weight Deflectometer and light Drop_weight for Quality Assessment During Road Formation and Foundation Construction[A]. TRB.80th Annual Meeting,2001
[16]Scrivner F H, Michalak C H, Moore W M. Calculation of the elastic moduli of a two-layer pavement system from measured surface deflection[J]. Highway Research Record No.431,1973.
[17]Yih Hou T. Evaluation of layered material properties from measured surface deflections[D]. Ph. D. dissertation, University of Utah,1977.
[18]Ullidtz P. Computer simulation of pavement performance[R]. Report No.18, the Institute of Roads, Transport, and Town Planning, The Technical University of Denmark,1978.
[19]Lytton R L, Michalak C H. Flexible pavement deflection equation using elastic moduli and field measurements [R]. Research Report 207-7F, Texas Transportation Institute, Texas A&M University, College Station,TX,1979.
[20]Bentsen R A, Nazarian S, Harrison J A. Reliability testing of seven nondestructive pavement testing devices[R]. Nondestructive Testing of Pavements and Backcalculation of Moduh, ASTV STP 1026, A J. Bush Ⅲ and G.Y. Baladi, Eds., A merican Society for Testing and Materials, Philadelphia, 1989:41-58.
[21]Anderson M. A data base method for backcalculation of composite pavement layer moduli [R]. Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM STP 1026, A.G. Y ush Ⅲ and G.Y Baladi, Eds., A merican Society for Testing and Materials, Philadelphia,pp,1989:201-216.
[22]Lyton R L. Backcalculation of pavement layer properties[R]. Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM STP 1026, A J. Bush Ⅲ and G.Y. Baladi, Eds., American Society for Testing and Materials, Philadelphia,1989:7-38.
[23]Meier RW, Rix GJ. Backcalculation of flexible pavement moduli using artificial neural networks[J]. Transportation Research Record,1994,1448.
[24]Khazanovich L, Roesler J., DIPLOBACK:Neural-network-based backcalcula-tion program for composite pavements[J]. Transportation Research Record, 1997,1570.
[25]Fwa T F, Tan C Y, Chan W T. "Backcalculation analysis of pavement-layer moduli using genetic algorithms", Transportation Research Record,1997.
[26]Himeno K, Kameyama S, Kasahara A, Maruyama T. Backcalculation of pavement layer moduli using genetic algorithms[A]. Eighth International Conference on Asphalt Pavements,1997.
[27]倪富健,邓学钧.柔性路面结构层模量反算方法研究[J].中国公路学报,1994,S1：25-31.
[28]王旭东,秦勤.一种动态弯沉盆的模量反算方法[J].公路交通科技,1999, 16(1)：13-16.
[29]王复明,魏翠玲,周晶.路面结构的动态反分析[J].工程力学,2002,19(1)：121-124.
[30]Xu-dong Zha, Qi-sen Zhang. Study on backcalculation for pavement moduli using genetic algorithm[A]. Proceedings of the Third International Conference on Road and Airfield Pavement[C]. Beijing:People's Communications Publishing House,1998:530-537.
[31]查旭东,王秉纲.基于人工神经网络的路面模量反算[J].交通运输工程学报,2002,2(2)：12-15.
[32]查旭东,王秉纲.基于同伦方法的路面模量反算研究[J].中国公路学报,2003,16(1)：1-5.
[33]任劲松.圆砾土填筑铁路路基压实质量标准研究[J].石家庄铁道学院学报,1997,10(增)：33-38.
[34]林祖玖.高速公路路基粗粒土填筑压实工艺[J].西部探矿工程(岩土钻掘矿业工程).1999,11(增)：56-59.
[35]徐立东.土石混合非均质填方的压实质量检测方法初探[J].辽宁交通科技,1999,22：44-46.
[36]马骏.超粒径含量高的砂卵石填方压实质量控制标准[J].路基工程,2002,1：31-33.
[37]毛洪录.含砂低液限粉土路基压实标准的探讨[J].山东大学学报：工学版,2003(5)：593-596.
[38]吴志雄.高速公路填石路基的施工与质量控制[J].中外公路,2003,1：32-35.
[39]章国辉.高速铁路碎石土路基压实质量检测方法标准的研究[J].铁道建设,2003,4：1-8.
[40]吴明友.路基压实参数及其工程意义[J].铁道建筑,2004,1：1-5.
[41]黄卫东.高速公路土石混填路基压实质量控制与评价[J].重庆交通学院学报,1997,4：25-28.
[42]Moshe Livneh. Use of Falling Weight Deflectometer and light Drop-weight for Quality Assessment During Road Formation and Foundation Construction [A]. TRB.80th Annual Meeting,2001
[43]刘建华,乐金朝,王复明,李强.落锤式弯沉仪在道路施工质量控制中的应用[J].郑州大学学报(工学版),2002,23(2)：47-50.
[44]张键强,梁伟东,陈瑜.落锤式弯沉仪在开阳高速公路路基施工质量检测中的应用[J].公路,2003(8)：95-97.
[45]王瑞宜,黄耕,朱一鸣.手持式落锤弯沉仪用于路基强度评价的尝试[J].公路,2002,47(9)：108-110.
[46]王瑞宜,郑国梁,黄文通,等.用手持式落锤弯沉仪评价砂砾土类路基质量[J].中南公路工程,2005,30(3)：128-130.
[47]郑京杰.利用手持式落锤弯沉仪评价路基路面强度参数[J].公路,2006,8：17-21.
[48]刘俊峰,徐科,李智,王瑞安.利用PFWD评价路基施工质量均匀性[J].湖南交通科技,2005,32(3)：48-49.
[49]徐科.使用落锤式弯沉仪评价基层施工质量均匀性[J].山东建筑工程学院学报,2006,21(2)：112-115.
[50]职雨风.使用落锤式弯沉仪评价基层施工质量[J].安徽工业大学学报,2006,23：50-56.
[51]职雨风,徐科,张肖宁.路面基层施工质量均匀性评价方法研究[J].公路,2005,1：101-105.
[52]陈涛,王曙光.高速公路路基施工质量均匀性评价分析[J].北方交通,2009,7：42-44.
[53]Rada G. LTPP Seasonal Monitoring Program:Instrumentation Installation and Data Collection Guidelines[R]. Federal Highway Administration, Report No.FHWA-RD-94-110,1994.
[54]Jorge Augusto Ceratti. Seasonal Variations of a Subgrade Soil Resilient Modulus in Southern Brazil[A]. TRB.83th Annual Meeting.2004.
[55]Mostafa A, Abo-Hashema. Environmental Impacts on the Subgrade Resilient Modulus for Idaho Pavements[A]. TRB.81th Annual Meeting,2002.
[56]AASHTO. Guide for Design of Pavement Structures[S]. American Association of State Highway and Transportation Offcials,1993.
[57黄仰贤.路面分析与设计[M].北京：人民交通出版社,1998.
[58]沙庆林.公路压实与压实标准[M].北京：人民交通出版社,1999年.
[59]林绣贤.由土的性质确定土基回弹模量的方法[J].华东公路,1994(1)：67-72.
[60]刘树堂.路基回弹弯沉检测标准探讨[J].华东公路,1997,5：24-26.
[61]粱锡三.关于公路路基弯沉检验标准问题的探讨[J].公路,1994,3：11-12.
[62]樊英华.土基回弹模量、回弹弯沉、现场CBR之间的关系[J].山西交通科技,2001,144(增2)：34-35.
[63]赵明华,张长耀,肖鹤松.路基土回弹模量EO和野外承载比CBR研究[J].湖 南大学学报,1993,20(5)：107-111.
[64]刘麟德.成双公司路基外回弹模量及弯沉测试分析研究[J].水电工程研究,1993,1：45-48.
[65]梁锡三,孙长新,陆毅,谢欢天.关于公路路基弯沉验收标准的探讨[J].中南公路工程,1994,1：26-27
[66]侯定一,吴文凯.计算机控制野外回弹模量测量仪的研制[J].湖南交通科技,1995,21(1)：51-54.
[67]陈忠达,张登良.风积沙路基压实技术的研究[J].中国公路学报,1999,12(3)：13-17.
[68]唐伯明,邓学钧.落锤式弯沉仪(FWD)与贝克曼梁式弯沉仪(BB)的对比试验研究[J].中国公路学报,1990(3)：37-43.
[69]蔡良才,余定选.机场刚性道面下土基模量取值方法研究[J].中国公路学报,1992,5(2)：8-12.
[70]武和平.水泥混凝土路面设计回弹模量建议值的修正系数研究[J].中国公路学报,1998,11(4)：1-10.
[71]张伟仁.影响柔性路面厚度的主要参数及确定方法[J].公路交通科技,1999,27(3)：31-33.
[72]Tam WS, Brown S F. Back-analysed elastic stiffnesses:comparison between different evaluation procedures [A]. First International symposium on Nondestructive Testing of Pavements and Back-calculation of Moduli, June 29-30,1988. Baltimore, Maryland, USA.
[73]查旭东.公路路基回弹模量的研究[R].长沙：长沙理工大学,2004.
[74]朱照宏,王秉纲,郭大智.路面力学计算[M].北京：人民交通出版社,1988.
[75]Pan, E. (a). Static Response of a Transversely Isotropic and Layered Half-space to General Dislocation Sources[M]. Phys. Earth Planet. Inter.,1989,58:103-117.
[76]Pan, E. (b). Static Response of a Transversely Isotropic and Layered Half-space to General Surface Loads[M]. Phys. Earth Planet. Inter.,1989,54:353-363.
[77]Goldberg D E. Genetic algorithm in pipeline optimization[J]. J. of Computing in Civil Engineering,1987,1(2):128-141.
[78]Goldberg D E. The Design of Innovation, Lessons from and for Competent Genetic Algorithms[M]. Kluwer Academic Publishers, Boston, MA.2002.
[79]陈国良,王熙法,庄镇泉,王东生.遗传算法及其应用[M].北京：人民邮电出版社,1995.
[80]石玉.提高实数遗传算法数值优化效率的研究[D].南京：南京航空航天大学,2002.
[81]汪荣鑫.数理统计[M],西安：西安交通大学出版社,1986.
[82]Dorigo M, Maniezzo V, Colomi A. Positive Feedback as a Search Strategy[R]. Technical Report NO.91-016, Politecnico di Milano,Italy.1991.
[83]Dorigo M. Optimization, learning and natural Algorithms[D]. Ph.D. Thesis, Dipartimento di Elettronica, Politecnico di Milano, Italy; 1992.
[84]Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colonies[A], Proc.1st European Conf. Artificial Life[C]. Pans, France:Elsevier,1991,134-142.
[85]Colorni A, Dnrigo M, Maniezzo V. An investigation of some proper-ties of an ant algorithm [A]. Pros, of Parallel Problem Solving from Nature (PPSN)[C]. France:Elsevier,1992,509-520.
[86]Colorni A, Dorigo M, Maniezzo V. Trubian M., Belgian J. Ant system for job shop scheduling. Operations. Research. Statistics and Computer[J]. Science, 1994,34(1):39-53.
[87]Dorigo M, Gambardella L M. Ant colony system:A cooperative learning approach to the traveling salesman problem[J]. IEEE Trans Evol Comput,1997, 1:53-66.
[88]Costa D. Hertz A, Dubuis O. Imbedding of a sequential algorithm within an evolutionary algorithm for coloring problem in graphs[J]. Journal of Heuristics, 1995, (1):105-128.
[89]Gutijahr W J. A generalized convergence result for the graph based ant system[R]. Technical Report 99-09, Dept. of Statistics and Decision Support System, University of Vienna, Austria,1999.
[90]Gutijahr W J. A graph-based ant system and its convergence [J]. Future Generation Computer Systems,2000,16(8):872-888.
[91]段海滨.蚁群算法原理及其应用[M].北京：科学出版社,2005.
[92]段海滨,王道波.蚁群算法的全局收敛性研究及改进[J].系统工程与电子技术,2004,26(10)：1506-1509.
[93]段海滨.蚁群算法及其在高性能电动仿真转台参数优化中的应用报告[D].南京：南京航空航天大学,2005.
[94]张纪会,徐心和.一种新的进化算法-蚁群算法[J].系统工程理论与实践,1999,3：84-87.
[95]Ullidtz P. Pavement Analysis, Developments in Civil Engineering, Elsevier,1998, 19:48-52.
[96]Ullitdz P. Stresses and Strains in a Two-Dimensional Particulate Material[A]. 74th Annual Meeting of the Transportation Research Board, Washington D.C. 1998.
[97]查旭东.基于同伦方法的模量反算的研究[D].西安：长安大学,2002.
[98]伍爱华,李智勇.蚁群遗传算法的多目标优化[J].计算机工程,2008,34(8)：200-202.
[99]Abbattista F, Abbattista N, Capponetti L. An evolutionary and cooperative agents model for optimization[A]. Proceeding of the IEEE International conference on evolutionary computation,1995,2:668-671.
[100]周永华.实数编码遗传算法杂交算子组合研究[D].广州：华南理工大学,2003.
[101]Ancey C. Notebook Introduction to Fluid Rheology[D]. Ecole Polytechnique Federal e de Lausanne.2005.
[102]Anderson M. Backcalculation of Composite Pavement Payer Moduli[D]. PhD dissertation, The University of Kentucky, Kentucky,1988.
[103]Cho Y S, Lin F B. Spectral Analysis of Surface Wave Response of Multilayer Thin Cement Mortar Slab Structures with Finite Thickness[J]. NDT and E International,2001,34:115-122.
[104]De Jong K A. An analysis of the behavior of a Class of Genetic Adaptive Systems[J]. Dissertation Abstracts International,1975,36(10).
[105]Danish Road Institute. Verification of Flexible Pavement Response From a Field Test Report[R]. Report 121,2001.
[106]Daridi F, Kharma N, Salik J. Parameterless Genetic Algorithms:Review and Innovation[J]. IEEE Canadian Review,2004,47:19-23.
[107]Fwa T F, Tan C Y, Chan W T. Backcalculation Analysis of Pavement-Layer Moduli Using Genetic Algorithms[J]. Journal of the Transportation Research Board,2007,1570.
[108]Fwa T F, Rani T S. Seed Modulus Generation Algorithm for Backcalculation of Flexible Pavement Moduli[J]. Transportation Research Record 1905, TRB, National Research Council, Washington, D.C.,2005:117-127.
[109]George K P. Falling Weight Deflectometer for Estimating Subgrade Moduli [R], Mississippi Department of Transportation, Report No. MS-DOT-RD-03-153, 2003.
[110]Gustafson M. An Analysis of Diversity in Genetic Programming[D]. PhD dissertation, The University of Nottingham, United Kingdom,2004.
[111]Gutijahr W J. ACO algorithms with guaranteed convergence to the optimal solution[J]. Information Processing letters,2002,82(3):145-153.
[112]Holland J H. Concerning Efficient Adaptive Systems[M]. Yovits, M. C. Self-Organizing Systems. Washington:Spartan Books,1962:215-230.
[113]Holland J H. Adaptation in Natural and Artificial Systems, 1sted.1975,2nded, Cambridge, MA:MIT press,1992
[114]Li M, Wang H, Li P. Tasks mapping in multi-core based system:hybrid ACO&GA approach[A]. Proceedings of the 5th international conference on ASIC,2003,1:335-30.
[115]Kameyama S, Himeno K, Kasahara A, Maruyama T. Backcalculation of Pavement Layer Moduli using Genetic Algorithms[A].8th International Conference on Asphalt Pavements, University of Washington, Seattle, Washington,1998:1375-1385.
[116]Marco Dorigo, Vittorio Maniezzo, Alberto Colorni. Ant System Optimization by a Colony of cooperating Agents[J]. IEEE TRANSACTIONS ON SYSTEM MAN AND CYBERNETICS--PART B CYBERNETICS,1996,26(1):29-41
[117]Reddy M Amaranathe, Reddy K Sudhakar, Pandev B B. Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli[J]. The International Journal of Pavement Engineering,2004,5(2).
[118]Minqiang L, Jisong K. A New Non-monotone Fitness Scaling for Genetic Algorithm[J]. Progress in Natural Science,2001,11(8):622-630.
[119]Nune, Rakesha, K Jainm, Amaranatha Teddyk, Sudhakar Reddy. Artificial neural networks—genetic algorithm based model for backcalculation of pavement layer moduli [J]. The International Journal of Pavement Engineering, 2006,7(3).
[120]Pan E. Thermoelastic Deformation of a Transversely Isotropic and Layered Half-space by Surface Loads and Internal Sources[J]. Phys. Earth Planet. Inter., 1990,60:254-264.
[121]Pan E. Static Green's Functions in Multilayered Half-spaces[J]. Applied Mathematical Modeling,1997,21:509-521.
[122]Sunil Sharma, Animesh Das. Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network[J]. Canada Journal of Civil Engineering,2008,35:57-66.
[123]Reddy M A, Reddy K S, Pandey B B. Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli [J]. The International Journal of Pavement Engineering,2004,5(2):81-90.
[124]Stolle D. Pavement Displacement Sensitivity to Layer Moduli[J]. Canadian Geotechnical Journal,2002,39:1395-1398.
[125]Stuezle T, Dorigo M. A short convergence proof for a class of ant colony optimization algorithms [J]. IEEE Transactions on Evolutionary Computation, 2002,6(4):358-365.
[126]Shiraz D. Tayabji, Erland O. Lukanen. Nondestructive Testing of Pavements and Backcalculation of Moduli:Third Volume[M]. (ASTM International 2000)
[127]Tsai B, Kannekanti V, Harvey J T. Application of Genetic Algorithm in Asphalt Pavement Design[A]. Transportation Research Board, No.1891, National Research Council, Washington, D.C.,2004:112-120.
[128]Westergaard H M. A Problem of Elasticity Suggested by a Problem in Soil Mechanics:A Soft Material Reinforced by Numerous Strong Horizontal Sheets, Contributions to the Mechanics of Solids, Stephen Timoshenko 60th Anniversary Volume, Macmillian, New York,1938.:268-277.
[129]White T, Pagurek B, Oppacher F. ASGA:improving the ant system by integration with genetic algorithms [A]. Proceedings of the 3rd annual genetic programming conference.1998,610-617.
[130]Jiping Yang, WanHua Qiu. A measure of risk and a decision-making model based on expected utility and entropy [J]. European Journal of Operational Research,2005,164:792-799.
[131]黄仰贤,余定选,齐诚.路面分析与设计[M].北京：人民交通出版社,1985.
[132]洛特菲.扎德,阮达,黄崇福.模糊集与模糊信息粒理论[M].北京：北京师范大学出版社,2000.
[133]C.A.勃莱皮埃,A.J.费伦特,刘修禾.工程问题的计算机解法[M].北京：科学普及出版社,1986.
[134]陈宏建,陈崚,徐晓华,屠莉.改进的增强型蚁群算法[J].计算机工程,2005,31(2)：176-178.
[135]边肇棋,张学工.模式识别[M].北京：清华大学出版社,2000.
[136]邓建中,葛仁杰,程正兴.计算方法[M].西安：西安交通大学出版社,1992.
[137]丁建立,陈增强,袁著祉.遗传算法与蚂蚁算法的融合[J].计算机研究与进展,2003,40(9)：1351-1356.
[138]邓巍巍,王越男.Visual Fortran编程指南[M].北京：人民邮电出版社,2000.
[139]高惠漩.统计计算[M].北京：北京大学出版社,1996.
[140]高应才.数学物理方程及其数值解法[M].北京：高等教育出版社,1986.
[141]黄卫,张凡.单圆荷载下路面响应的近似计算[J].公路,1995,10：10-12.
[142]李朝阳,许志鸿.弹性四层体系显式化公式的研究[J].华东公路,1996,2：47-50.
[143]李守巨,刘迎曦,孙伟.智能计算与参数反演[M].北京：科学出版社,2008.
[144]廖正环,唐勇,凌天清,高建平.公路工程实用电算[M].北京：人民交通出版社,1999.
[145]陆明万,罗学富.弹性理论基础[M].北京：清华大学出版社,1990.
[146]明亮.遗传算法的模式理论及收敛定理[D].西安：西安电子科技大学,2006.
[147]王秉纲,邓学钧.路面力学数值计算[M].北京：人民交通出版社,1992.
[148]王光远,董明耀.结构优化设计[M].北京：高等教育出版社,1987.
[149]吴文海,王学坤,许志鸿.柔性路面结构轮间路表弯沉逼近式的研究[J].同济大学学报(自然科学版),1994,22(1)：41-46.
[150]奚定平.贝塞尔函数[M].北京：高等教育出版社,1998.
[151]徐芝纶.弹性力学(第二版上、下册)[M].北京：高等教育出版社,1988.
[152]阎平凡,张长水.人工神经网络与模拟进化计算[M].北京：清华大学出版社,2000.
[153]杨冰.实用最优化方法及计算机程序[M].哈尔滨：哈尔滨船舶工程学院出版社,1994.
[154]查旭东,张起森.基于神经网络理论的三层体系弯沉拟合的研究[J].长沙交通学院学报,1999,15(3)：48-52.
[155]查旭东.基于神经网络理论的沥青路面结构四层体系弯沉的拟合研究[J].西安公路交通大学学报,2000,20(1)：5-15.
[156]张可村.工程优化的算法与分析[M].西安：西安交通大学出版,1989.
[157]张文修,梁怡.遗传算法的数学基础[M].西安：西安交通大学出版社,2000.
[158]赵振宇,徐用愚.模糊理论和神经网络的基础与应用[M].北京：清华大学出版社,1996.
[159]张筑生著.微分动力系统原理[M].北京：科学出版社,1999.
[160]Vapnik V N. Statistical Learning Theory[M].Wiley, New York,1998.
[161]成礼智,王红霞,罗永.小波理论与应用[M].北京：科学出版社,2006.
[162]Girosi F, Jones M, Poggio T. Regularization theory and neural networks architectures [J]. Neural Comput.1995,7:219-269.
[163]Jean Duchon. Splines minimizing rotation-invariant semi-norms in Sobolev Spaces[J]. Springer Berlin/Heidelberg.1977.
[164]Trevor Hastie, Robert Tibshirani, Jerome Friedman. the Element of Statistical Learnin[J]. Springer,2008.
[165]Vapnik V N, Ya A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities [J]. Th. Prob. and its Applications, 1971,17(2):264-280.
[166]樊兆强,杨辉,攸频.落锤式弯沉仪与贝克曼梁式弯沉仪的比较和评价[J].中国市政工程,2003,5：8-10.
[167]Markowitz H. Portfolio selection[J]. Journal of Finance,1052,7:77-91.
[168]Ross S. Random Simulations[M]. Springer,2006.
[169]Wahba G. Splines Models for Observational Data[M]. Series in Applied Mathematics, Vol.59 Philadelphia:SIAM, PA,1990.
[170]Peter J. Rousseeuw, Annick M. Leroy. Robust Regression and Outlier Detection[M]. Wiley,2003.
[171]Theodors Evgenion, Massimiliano Pontil, Tomaso Paggio. Regularization Networks and Support Vector Machines [J]. In Comput Math, (2000),13:1-50.
[172]Jun Shao, Mathematical Statistics[M]. Springer,2003.
[173]Dyn N, Jackson I R H, Row A. On multivariate approximation by integer translates of a basis function [J]. J. of Math,1992(78):95-130.
[174]中华人民共和国交通部行业标准.公路沥青路面设计规范(JTG D50-2006) [S].北京：人民交通出版社,2006.
[175]中华人民共和国交通部部标准.公路柔性路面设计规范(JTJ 014-86)[S].北京：人民交通出版社,1987.
[176]中华人民共和国交通部行业标准.公路土工试验规程(JTG E40-2007) [S].北京：人民交通出版社,2007.
[177]中华人民共和国交通部行业标准.公路路基路面现场测试规程(JTG E60-2008) [S].北京：人民交通出版社,2008.
[178]中华人民共和国交通部行业标准.公路水泥混凝土路面设计规范(JTG D40-2002) [S].北京：人民交通出版社,2003.
[179]中华人民共和国行业标准.土工试验规程(SL 237-1999) [S].北京：中国水 利水电出版社,1999.
[180]中华人民共和国交通部行业标准.公路路基设计规范(JTG D30—2004) [S].北京：人民交通出版社,2004.
[181]中华人民共和国交通部行业标准.公路路基施工技术规范(JTG F10-2006) [S].北京：人民交通出版社,2006.
[182]高速公路丛书编委会.高速公路路基设计与施工[M].北京：人民交通出版社,1998.
[183]袁志发,周静芋.多元统计分析[M].北京：科学出版社,2003.
[2]杨永红.甘肃黄土地区土基回弹模量[J].长安大学学报(自然科学版),2005,25(3)：7-10.
[3]叶燕呼.广东省公路路基土强度及其分级研究[J].公路,2000,3：14-20.
[4]吴德华.陕西关中地区土基回弹模量研究[J].公路交通科技,2005,22(2)：27-30.
[5]沈金安.国外沥青路面设计方法总汇[M].北京：人民交通出版社,2004.
[6]邓露.路基土的CBR强度与压实度关系的试验研究[J].华中科技大学学报,2005,22(增刊)：109-115.
[7]陈晓光.新疆高等级公路半刚性基层土基强度等级划分[J].公路交通科技,1999,16(3)：13-16.
[8]李喜安.公路黄土路基动力学参数的影响因素及其规律研究[J].公路交通科技,2005,22(6)：87-91.
[9]杨广庆.细粒土路基的弹性模量[J].路基工程,2000,91(4)：42-44.
[10]卢永贵.成都粘土及其石灰稳定土的动力特性试验研究[J].路基工程,1998,77(2)：34-37.
[11]张洪华.应用FWD测定土基回弹模量的研究[J].中国公路学报,1994,17(增1期)：9-13.
[12]George K P. Subgrade Characterization Employing the Falling Weight Deflectometer[A]. TRB.82th Annual Meeting,2003
[13]Chai G. The Structural Response and Behavior Prediction of Subgrade Soils Using Falling Weight Deflectometer in Pavement Construction [A]. Proceedings,Third International Conference on Road & Airfield Pavement Technology, Beijing, China,1998.
[14]王端宜.手持式落锤式弯沉仪用于路基强度评价的尝试[J].公路,2002,9：108-110.
[15]Livneh M. Use of Falling Weight Deflectometer and light Drop_weight for Quality Assessment During Road Formation and Foundation Construction[A]. TRB.80th Annual Meeting,2001
[16]Scrivner F H, Michalak C H, Moore W M. Calculation of the elastic moduli of a two-layer pavement system from measured surface deflection[J]. Highway Research Record No.431,1973.
[17]Yih Hou T. Evaluation of layered material properties from measured surface deflections[D]. Ph. D. dissertation, University of Utah,1977.
[18]Ullidtz P. Computer simulation of pavement performance[R]. Report No.18, the Institute of Roads, Transport, and Town Planning, The Technical University of Denmark,1978.
[19]Lytton R L, Michalak C H. Flexible pavement deflection equation using elastic moduli and field measurements [R]. Research Report 207-7F, Texas Transportation Institute, Texas A&M University, College Station,TX,1979.
[20]Bentsen R A, Nazarian S, Harrison J A. Reliability testing of seven nondestructive pavement testing devices[R]. Nondestructive Testing of Pavements and Backcalculation of Moduh, ASTV STP 1026, A J. Bush Ⅲ and G.Y. Baladi, Eds., A merican Society for Testing and Materials, Philadelphia, 1989:41-58.
[21]Anderson M. A data base method for backcalculation of composite pavement layer moduli [R]. Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM STP 1026, A.G. Y ush Ⅲ and G.Y Baladi, Eds., A merican Society for Testing and Materials, Philadelphia,pp,1989:201-216.
[22]Lyton R L. Backcalculation of pavement layer properties[R]. Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM STP 1026, A J. Bush Ⅲ and G.Y. Baladi, Eds., American Society for Testing and Materials, Philadelphia,1989:7-38.
[23]Meier RW, Rix GJ. Backcalculation of flexible pavement moduli using artificial neural networks[J]. Transportation Research Record,1994,1448.
[24]Khazanovich L, Roesler J., DIPLOBACK:Neural-network-based backcalcula-tion program for composite pavements[J]. Transportation Research Record, 1997,1570.
[25]Fwa T F, Tan C Y, Chan W T. "Backcalculation analysis of pavement-layer moduli using genetic algorithms", Transportation Research Record,1997.
[26]Himeno K, Kameyama S, Kasahara A, Maruyama T. Backcalculation of pavement layer moduli using genetic algorithms[A]. Eighth International Conference on Asphalt Pavements,1997.
[27]倪富健,邓学钧.柔性路面结构层模量反算方法研究[J].中国公路学报,1994,S1：25-31.
[28]王旭东,秦勤.一种动态弯沉盆的模量反算方法[J].公路交通科技,1999, 16(1)：13-16.
[29]王复明,魏翠玲,周晶.路面结构的动态反分析[J].工程力学,2002,19(1)：121-124.
[30]Xu-dong Zha, Qi-sen Zhang. Study on backcalculation for pavement moduli using genetic algorithm[A]. Proceedings of the Third International Conference on Road and Airfield Pavement[C]. Beijing:People's Communications Publishing House,1998:530-537.
[31]查旭东,王秉纲.基于人工神经网络的路面模量反算[J].交通运输工程学报,2002,2(2)：12-15.
[32]查旭东,王秉纲.基于同伦方法的路面模量反算研究[J].中国公路学报,2003,16(1)：1-5.
[33]任劲松.圆砾土填筑铁路路基压实质量标准研究[J].石家庄铁道学院学报,1997,10(增)：33-38.
[34]林祖玖.高速公路路基粗粒土填筑压实工艺[J].西部探矿工程(岩土钻掘矿业工程).1999,11(增)：56-59.
[35]徐立东.土石混合非均质填方的压实质量检测方法初探[J].辽宁交通科技,1999,22：44-46.
[36]马骏.超粒径含量高的砂卵石填方压实质量控制标准[J].路基工程,2002,1：31-33.
[37]毛洪录.含砂低液限粉土路基压实标准的探讨[J].山东大学学报：工学版,2003(5)：593-596.
[38]吴志雄.高速公路填石路基的施工与质量控制[J].中外公路,2003,1：32-35.
[39]章国辉.高速铁路碎石土路基压实质量检测方法标准的研究[J].铁道建设,2003,4：1-8.
[40]吴明友.路基压实参数及其工程意义[J].铁道建筑,2004,1：1-5.
[41]黄卫东.高速公路土石混填路基压实质量控制与评价[J].重庆交通学院学报,1997,4：25-28.
[42]Moshe Livneh. Use of Falling Weight Deflectometer and light Drop-weight for Quality Assessment During Road Formation and Foundation Construction [A]. TRB.80th Annual Meeting,2001
[43]刘建华,乐金朝,王复明,李强.落锤式弯沉仪在道路施工质量控制中的应用[J].郑州大学学报(工学版),2002,23(2)：47-50.
[44]张键强,梁伟东,陈瑜.落锤式弯沉仪在开阳高速公路路基施工质量检测中的应用[J].公路,2003(8)：95-97.
[45]王瑞宜,黄耕,朱一鸣.手持式落锤弯沉仪用于路基强度评价的尝试[J].公路,2002,47(9)：108-110.
[46]王瑞宜,郑国梁,黄文通,等.用手持式落锤弯沉仪评价砂砾土类路基质量[J].中南公路工程,2005,30(3)：128-130.
[47]郑京杰.利用手持式落锤弯沉仪评价路基路面强度参数[J].公路,2006,8：17-21.
[48]刘俊峰,徐科,李智,王瑞安.利用PFWD评价路基施工质量均匀性[J].湖南交通科技,2005,32(3)：48-49.
[49]徐科.使用落锤式弯沉仪评价基层施工质量均匀性[J].山东建筑工程学院学报,2006,21(2)：112-115.
[50]职雨风.使用落锤式弯沉仪评价基层施工质量[J].安徽工业大学学报,2006,23：50-56.
[51]职雨风,徐科,张肖宁.路面基层施工质量均匀性评价方法研究[J].公路,2005,1：101-105.
[52]陈涛,王曙光.高速公路路基施工质量均匀性评价分析[J].北方交通,2009,7：42-44.
[53]Rada G. LTPP Seasonal Monitoring Program:Instrumentation Installation and Data Collection Guidelines[R]. Federal Highway Administration, Report No.FHWA-RD-94-110,1994.
[54]Jorge Augusto Ceratti. Seasonal Variations of a Subgrade Soil Resilient Modulus in Southern Brazil[A]. TRB.83th Annual Meeting.2004.
[55]Mostafa A, Abo-Hashema. Environmental Impacts on the Subgrade Resilient Modulus for Idaho Pavements[A]. TRB.81th Annual Meeting,2002.
[56]AASHTO. Guide for Design of Pavement Structures[S]. American Association of State Highway and Transportation Offcials,1993.
[57黄仰贤.路面分析与设计[M].北京：人民交通出版社,1998.
[58]沙庆林.公路压实与压实标准[M].北京：人民交通出版社,1999年.
[59]林绣贤.由土的性质确定土基回弹模量的方法[J].华东公路,1994(1)：67-72.
[60]刘树堂.路基回弹弯沉检测标准探讨[J].华东公路,1997,5：24-26.
[61]粱锡三.关于公路路基弯沉检验标准问题的探讨[J].公路,1994,3：11-12.
[62]樊英华.土基回弹模量、回弹弯沉、现场CBR之间的关系[J].山西交通科技,2001,144(增2)：34-35.
[63]赵明华,张长耀,肖鹤松.路基土回弹模量EO和野外承载比CBR研究[J].湖 南大学学报,1993,20(5)：107-111.
[64]刘麟德.成双公司路基外回弹模量及弯沉测试分析研究[J].水电工程研究,1993,1：45-48.
[65]梁锡三,孙长新,陆毅,谢欢天.关于公路路基弯沉验收标准的探讨[J].中南公路工程,1994,1：26-27
[66]侯定一,吴文凯.计算机控制野外回弹模量测量仪的研制[J].湖南交通科技,1995,21(1)：51-54.
[67]陈忠达,张登良.风积沙路基压实技术的研究[J].中国公路学报,1999,12(3)：13-17.
[68]唐伯明,邓学钧.落锤式弯沉仪(FWD)与贝克曼梁式弯沉仪(BB)的对比试验研究[J].中国公路学报,1990(3)：37-43.
[69]蔡良才,余定选.机场刚性道面下土基模量取值方法研究[J].中国公路学报,1992,5(2)：8-12.
[70]武和平.水泥混凝土路面设计回弹模量建议值的修正系数研究[J].中国公路学报,1998,11(4)：1-10.
[71]张伟仁.影响柔性路面厚度的主要参数及确定方法[J].公路交通科技,1999,27(3)：31-33.
[72]Tam WS, Brown S F. Back-analysed elastic stiffnesses:comparison between different evaluation procedures [A]. First International symposium on Nondestructive Testing of Pavements and Back-calculation of Moduli, June 29-30,1988. Baltimore, Maryland, USA.
[73]查旭东.公路路基回弹模量的研究[R].长沙：长沙理工大学,2004.
[74]朱照宏,王秉纲,郭大智.路面力学计算[M].北京：人民交通出版社,1988.
[75]Pan, E. (a). Static Response of a Transversely Isotropic and Layered Half-space to General Dislocation Sources[M]. Phys. Earth Planet. Inter.,1989,58:103-117.
[76]Pan, E. (b). Static Response of a Transversely Isotropic and Layered Half-space to General Surface Loads[M]. Phys. Earth Planet. Inter.,1989,54:353-363.
[77]Goldberg D E. Genetic algorithm in pipeline optimization[J]. J. of Computing in Civil Engineering,1987,1(2):128-141.
[78]Goldberg D E. The Design of Innovation, Lessons from and for Competent Genetic Algorithms[M]. Kluwer Academic Publishers, Boston, MA.2002.
[79]陈国良,王熙法,庄镇泉,王东生.遗传算法及其应用[M].北京：人民邮电出版社,1995.
[80]石玉.提高实数遗传算法数值优化效率的研究[D].南京：南京航空航天大学,2002.
[81]汪荣鑫.数理统计[M],西安：西安交通大学出版社,1986.
[82]Dorigo M, Maniezzo V, Colomi A. Positive Feedback as a Search Strategy[R]. Technical Report NO.91-016, Politecnico di Milano,Italy.1991.
[83]Dorigo M. Optimization, learning and natural Algorithms[D]. Ph.D. Thesis, Dipartimento di Elettronica, Politecnico di Milano, Italy; 1992.
[84]Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colonies[A], Proc.1st European Conf. Artificial Life[C]. Pans, France:Elsevier,1991,134-142.
[85]Colorni A, Dnrigo M, Maniezzo V. An investigation of some proper-ties of an ant algorithm [A]. Pros, of Parallel Problem Solving from Nature (PPSN)[C]. France:Elsevier,1992,509-520.
[86]Colorni A, Dorigo M, Maniezzo V. Trubian M., Belgian J. Ant system for job shop scheduling. Operations. Research. Statistics and Computer[J]. Science, 1994,34(1):39-53.
[87]Dorigo M, Gambardella L M. Ant colony system:A cooperative learning approach to the traveling salesman problem[J]. IEEE Trans Evol Comput,1997, 1:53-66.
[88]Costa D. Hertz A, Dubuis O. Imbedding of a sequential algorithm within an evolutionary algorithm for coloring problem in graphs[J]. Journal of Heuristics, 1995, (1):105-128.
[89]Gutijahr W J. A generalized convergence result for the graph based ant system[R]. Technical Report 99-09, Dept. of Statistics and Decision Support System, University of Vienna, Austria,1999.
[90]Gutijahr W J. A graph-based ant system and its convergence [J]. Future Generation Computer Systems,2000,16(8):872-888.
[91]段海滨.蚁群算法原理及其应用[M].北京：科学出版社,2005.
[92]段海滨,王道波.蚁群算法的全局收敛性研究及改进[J].系统工程与电子技术,2004,26(10)：1506-1509.
[93]段海滨.蚁群算法及其在高性能电动仿真转台参数优化中的应用报告[D].南京：南京航空航天大学,2005.
[94]张纪会,徐心和.一种新的进化算法-蚁群算法[J].系统工程理论与实践,1999,3：84-87.
[95]Ullidtz P. Pavement Analysis, Developments in Civil Engineering, Elsevier,1998, 19:48-52.
[96]Ullitdz P. Stresses and Strains in a Two-Dimensional Particulate Material[A]. 74th Annual Meeting of the Transportation Research Board, Washington D.C. 1998.
[97]查旭东.基于同伦方法的模量反算的研究[D].西安：长安大学,2002.
[98]伍爱华,李智勇.蚁群遗传算法的多目标优化[J].计算机工程,2008,34(8)：200-202.
[99]Abbattista F, Abbattista N, Capponetti L. An evolutionary and cooperative agents model for optimization[A]. Proceeding of the IEEE International conference on evolutionary computation,1995,2:668-671.
[100]周永华.实数编码遗传算法杂交算子组合研究[D].广州：华南理工大学,2003.
[101]Ancey C. Notebook Introduction to Fluid Rheology[D]. Ecole Polytechnique Federal e de Lausanne.2005.
[102]Anderson M. Backcalculation of Composite Pavement Payer Moduli[D]. PhD dissertation, The University of Kentucky, Kentucky,1988.
[103]Cho Y S, Lin F B. Spectral Analysis of Surface Wave Response of Multilayer Thin Cement Mortar Slab Structures with Finite Thickness[J]. NDT and E International,2001,34:115-122.
[104]De Jong K A. An analysis of the behavior of a Class of Genetic Adaptive Systems[J]. Dissertation Abstracts International,1975,36(10).
[105]Danish Road Institute. Verification of Flexible Pavement Response From a Field Test Report[R]. Report 121,2001.
[106]Daridi F, Kharma N, Salik J. Parameterless Genetic Algorithms:Review and Innovation[J]. IEEE Canadian Review,2004,47:19-23.
[107]Fwa T F, Tan C Y, Chan W T. Backcalculation Analysis of Pavement-Layer Moduli Using Genetic Algorithms[J]. Journal of the Transportation Research Board,2007,1570.
[108]Fwa T F, Rani T S. Seed Modulus Generation Algorithm for Backcalculation of Flexible Pavement Moduli[J]. Transportation Research Record 1905, TRB, National Research Council, Washington, D.C.,2005:117-127.
[109]George K P. Falling Weight Deflectometer for Estimating Subgrade Moduli [R], Mississippi Department of Transportation, Report No. MS-DOT-RD-03-153, 2003.
[110]Gustafson M. An Analysis of Diversity in Genetic Programming[D]. PhD dissertation, The University of Nottingham, United Kingdom,2004.
[111]Gutijahr W J. ACO algorithms with guaranteed convergence to the optimal solution[J]. Information Processing letters,2002,82(3):145-153.
[112]Holland J H. Concerning Efficient Adaptive Systems[M]. Yovits, M. C. Self-Organizing Systems. Washington:Spartan Books,1962:215-230.
[113]Holland J H. Adaptation in Natural and Artificial Systems, 1sted.1975,2nded, Cambridge, MA:MIT press,1992
[114]Li M, Wang H, Li P. Tasks mapping in multi-core based system:hybrid ACO&GA approach[A]. Proceedings of the 5th international conference on ASIC,2003,1:335-30.
[115]Kameyama S, Himeno K, Kasahara A, Maruyama T. Backcalculation of Pavement Layer Moduli using Genetic Algorithms[A].8th International Conference on Asphalt Pavements, University of Washington, Seattle, Washington,1998:1375-1385.
[116]Marco Dorigo, Vittorio Maniezzo, Alberto Colorni. Ant System Optimization by a Colony of cooperating Agents[J]. IEEE TRANSACTIONS ON SYSTEM MAN AND CYBERNETICS--PART B CYBERNETICS,1996,26(1):29-41
[117]Reddy M Amaranathe, Reddy K Sudhakar, Pandev B B. Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli[J]. The International Journal of Pavement Engineering,2004,5(2).
[118]Minqiang L, Jisong K. A New Non-monotone Fitness Scaling for Genetic Algorithm[J]. Progress in Natural Science,2001,11(8):622-630.
[119]Nune, Rakesha, K Jainm, Amaranatha Teddyk, Sudhakar Reddy. Artificial neural networks—genetic algorithm based model for backcalculation of pavement layer moduli [J]. The International Journal of Pavement Engineering, 2006,7(3).
[120]Pan E. Thermoelastic Deformation of a Transversely Isotropic and Layered Half-space by Surface Loads and Internal Sources[J]. Phys. Earth Planet. Inter., 1990,60:254-264.
[121]Pan E. Static Green's Functions in Multilayered Half-spaces[J]. Applied Mathematical Modeling,1997,21:509-521.
[122]Sunil Sharma, Animesh Das. Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network[J]. Canada Journal of Civil Engineering,2008,35:57-66.
[123]Reddy M A, Reddy K S, Pandey B B. Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli [J]. The International Journal of Pavement Engineering,2004,5(2):81-90.
[124]Stolle D. Pavement Displacement Sensitivity to Layer Moduli[J]. Canadian Geotechnical Journal,2002,39:1395-1398.
[125]Stuezle T, Dorigo M. A short convergence proof for a class of ant colony optimization algorithms [J]. IEEE Transactions on Evolutionary Computation, 2002,6(4):358-365.
[126]Shiraz D. Tayabji, Erland O. Lukanen. Nondestructive Testing of Pavements and Backcalculation of Moduli:Third Volume[M]. (ASTM International 2000)
[127]Tsai B, Kannekanti V, Harvey J T. Application of Genetic Algorithm in Asphalt Pavement Design[A]. Transportation Research Board, No.1891, National Research Council, Washington, D.C.,2004:112-120.
[128]Westergaard H M. A Problem of Elasticity Suggested by a Problem in Soil Mechanics:A Soft Material Reinforced by Numerous Strong Horizontal Sheets, Contributions to the Mechanics of Solids, Stephen Timoshenko 60th Anniversary Volume, Macmillian, New York,1938.:268-277.
[129]White T, Pagurek B, Oppacher F. ASGA:improving the ant system by integration with genetic algorithms [A]. Proceedings of the 3rd annual genetic programming conference.1998,610-617.
[130]Jiping Yang, WanHua Qiu. A measure of risk and a decision-making model based on expected utility and entropy [J]. European Journal of Operational Research,2005,164:792-799.
[131]黄仰贤,余定选,齐诚.路面分析与设计[M].北京：人民交通出版社,1985.
[132]洛特菲.扎德,阮达,黄崇福.模糊集与模糊信息粒理论[M].北京：北京师范大学出版社,2000.
[133]C.A.勃莱皮埃,A.J.费伦特,刘修禾.工程问题的计算机解法[M].北京：科学普及出版社,1986.
[134]陈宏建,陈崚,徐晓华,屠莉.改进的增强型蚁群算法[J].计算机工程,2005,31(2)：176-178.
[135]边肇棋,张学工.模式识别[M].北京：清华大学出版社,2000.
[136]邓建中,葛仁杰,程正兴.计算方法[M].西安：西安交通大学出版社,1992.
[137]丁建立,陈增强,袁著祉.遗传算法与蚂蚁算法的融合[J].计算机研究与进展,2003,40(9)：1351-1356.
[138]邓巍巍,王越男.Visual Fortran编程指南[M].北京：人民邮电出版社,2000.
[139]高惠漩.统计计算[M].北京：北京大学出版社,1996.
[140]高应才.数学物理方程及其数值解法[M].北京：高等教育出版社,1986.
[141]黄卫,张凡.单圆荷载下路面响应的近似计算[J].公路,1995,10：10-12.
[142]李朝阳,许志鸿.弹性四层体系显式化公式的研究[J].华东公路,1996,2：47-50.
[143]李守巨,刘迎曦,孙伟.智能计算与参数反演[M].北京：科学出版社,2008.
[144]廖正环,唐勇,凌天清,高建平.公路工程实用电算[M].北京：人民交通出版社,1999.
[145]陆明万,罗学富.弹性理论基础[M].北京：清华大学出版社,1990.
[146]明亮.遗传算法的模式理论及收敛定理[D].西安：西安电子科技大学,2006.
[147]王秉纲,邓学钧.路面力学数值计算[M].北京：人民交通出版社,1992.
[148]王光远,董明耀.结构优化设计[M].北京：高等教育出版社,1987.
[149]吴文海,王学坤,许志鸿.柔性路面结构轮间路表弯沉逼近式的研究[J].同济大学学报(自然科学版),1994,22(1)：41-46.
[150]奚定平.贝塞尔函数[M].北京：高等教育出版社,1998.
[151]徐芝纶.弹性力学(第二版上、下册)[M].北京：高等教育出版社,1988.
[152]阎平凡,张长水.人工神经网络与模拟进化计算[M].北京：清华大学出版社,2000.
[153]杨冰.实用最优化方法及计算机程序[M].哈尔滨：哈尔滨船舶工程学院出版社,1994.
[154]查旭东,张起森.基于神经网络理论的三层体系弯沉拟合的研究[J].长沙交通学院学报,1999,15(3)：48-52.
[155]查旭东.基于神经网络理论的沥青路面结构四层体系弯沉的拟合研究[J].西安公路交通大学学报,2000,20(1)：5-15.
[156]张可村.工程优化的算法与分析[M].西安：西安交通大学出版,1989.
[157]张文修,梁怡.遗传算法的数学基础[M].西安：西安交通大学出版社,2000.
[158]赵振宇,徐用愚.模糊理论和神经网络的基础与应用[M].北京：清华大学出版社,1996.
[159]张筑生著.微分动力系统原理[M].北京：科学出版社,1999.
[160]Vapnik V N. Statistical Learning Theory[M].Wiley, New York,1998.
[161]成礼智,王红霞,罗永.小波理论与应用[M].北京：科学出版社,2006.
[162]Girosi F, Jones M, Poggio T. Regularization theory and neural networks architectures [J]. Neural Comput.1995,7:219-269.
[163]Jean Duchon. Splines minimizing rotation-invariant semi-norms in Sobolev Spaces[J]. Springer Berlin/Heidelberg.1977.
[164]Trevor Hastie, Robert Tibshirani, Jerome Friedman. the Element of Statistical Learnin[J]. Springer,2008.
[165]Vapnik V N, Ya A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities [J]. Th. Prob. and its Applications, 1971,17(2):264-280.
[166]樊兆强,杨辉,攸频.落锤式弯沉仪与贝克曼梁式弯沉仪的比较和评价[J].中国市政工程,2003,5：8-10.
[167]Markowitz H. Portfolio selection[J]. Journal of Finance,1052,7:77-91.
[168]Ross S. Random Simulations[M]. Springer,2006.
[169]Wahba G. Splines Models for Observational Data[M]. Series in Applied Mathematics, Vol.59 Philadelphia:SIAM, PA,1990.
[170]Peter J. Rousseeuw, Annick M. Leroy. Robust Regression and Outlier Detection[M]. Wiley,2003.
[171]Theodors Evgenion, Massimiliano Pontil, Tomaso Paggio. Regularization Networks and Support Vector Machines [J]. In Comput Math, (2000),13:1-50.
[172]Jun Shao, Mathematical Statistics[M]. Springer,2003.
[173]Dyn N, Jackson I R H, Row A. On multivariate approximation by integer translates of a basis function [J]. J. of Math,1992(78):95-130.
[174]中华人民共和国交通部行业标准.公路沥青路面设计规范(JTG D50-2006) [S].北京：人民交通出版社,2006.
[175]中华人民共和国交通部部标准.公路柔性路面设计规范(JTJ 014-86)[S].北京：人民交通出版社,1987.
[176]中华人民共和国交通部行业标准.公路土工试验规程(JTG E40-2007) [S].北京：人民交通出版社,2007.
[177]中华人民共和国交通部行业标准.公路路基路面现场测试规程(JTG E60-2008) [S].北京：人民交通出版社,2008.
[178]中华人民共和国交通部行业标准.公路水泥混凝土路面设计规范(JTG D40-2002) [S].北京：人民交通出版社,2003.
[179]中华人民共和国行业标准.土工试验规程(SL 237-1999) [S].北京：中国水 利水电出版社,1999.
[180]中华人民共和国交通部行业标准.公路路基设计规范(JTG D30—2004) [S].北京：人民交通出版社,2004.
[181]中华人民共和国交通部行业标准.公路路基施工技术规范(JTG F10-2006) [S].北京：人民交通出版社,2006.
[182]高速公路丛书编委会.高速公路路基设计与施工[M].北京：人民交通出版社,1998.
[183]袁志发,周静芋.多元统计分析[M].北京：科学出版社,2003.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |