基于现代技术的河道浅滩演变研究
|
摘要
河道浅滩演变研究是河流动力学的重要组成部分，是水利学科的基础性课题，也是进行水利、水运工程规划、设计、管理和工程可行性研究的基础工作。作者结合工程实例，以现代科学技术手段研究河道浅滩演变，主要内容如下：
第一部分以RS技术为手段，建立闽江竹岐至侯官河段遥感信息与水深之间的数学模型。研究表明，用最低通航设计水位时的水域边界裁取研究水域，可消除边界点因水陆信息混合产生的误差，提高遥感水深精度。
第二部分对人工神经网络理论进行了简要概括，对BP网络的原理进行了分析。在分析影响河道浅滩演变因素的基础上，提出了基于BP神经网络的河道浅滩演变预测模型，分析并确定了模型的输入、输出因子，提出各因子的获取方法以及训练样本选取方法，并对BP网络设计进行了探讨。以闽江竹岐至侯官河段为实例，计算结果表明，模型预测结果与实际值吻合良好。这为河道浅滩演变预测研究提供了一种新方法。
第三部分对GIS与平面二维泥沙数学模型集成意义、问题和方法进行了分析。在此基础上，建立了基于GIS的泥沙数学模型，设计了两种模式数据交换的接口程序，探讨了泥沙模型计算域空间离散问题。最后成功地对闽江竹岐至侯官河段进行了整治工程效果预测，所得结果被航道部门采用。
在第四部分的研究中，以VB和GIS为开发工具，针对闽江竹岐至侯官河段研究中的二种模型，集成开发了浅滩演变分析的模拟与预测系统，设计了系统的总体结构，探讨了系统功能和系统关键技术的实现。
本文各章不仅进行了理论研究，同时还结合交通部人材基金项目和闽江水口坝下航道整治项目和闽江航道信息管理系统项目进行了应用研究。本文的研究是对水利学科中浅滩演变预测研究的一次新探索，且具有很好的应用前景。
Studying on river shoal evolution is a fundamental work in the science of water conservancy, water conservancy projects and waterways planning, designing, management and engineering feasibility. In this paper, river shoal evolution is studied by means of modern science and technique, combined with the real projects. Particular contents are presented as follow.
In Part I , the mathematical model between remote sensing image spectral value and survey water-depth is built in Zhuqi-Houguan of Minjiang river by remote sensing (RS). It is proved that the error caused by mixing water-land information on boundary may be eliminated by choosing the research waters within the water boundary under designed lowest navigable stage, and the precision of remote water-depth of river may be enhanced.
In Part II, the theory of artificial neural network (ANN) is introduced briefly, the principle of back propagation(BP) neural network is analyzed. River shoal evolution prediction models on a BP neural network are established on analyzing factors affecting shoal evolution in a river, and input as well as output factors are determined by analyzing, the methods of obtaining these factors and selecting training samples are presented, and the designing of a BP network is also studied. The predicted result showed good agreement with field data in Zhouqi-Houguan of Minjiang river.
In Part III, the significance, problem and methods of integrating plane 2-D sediment mathematical model with geographical information system (GIS) are discussed . The mathematical model based on GIS is built, and the interface program of data conversion between the two models is designed, and the spatial discretion of the computational domain is discussed. The model is used to predict the influence of regulation work on shoal evolution in Zhouqi-Houguan of Minjiang river, and the results are adopted by the department of responsibility conservancy.
In Part IV, the system of simulating and predicting is developed by mean of a Visual Basic and GIS ,according to the two shoal evolution prediction models in Zhouqi-Houguan of Minjiang river. The general framework is designed, the schemes of some critical techniques of the platform such as data interface and model-creating techniques are presented, then the main functions and platform are outlined.
The work in this paper is concerned with the theoretical method, combined with the projects of regulation work of waterway and management information system in Zhouqi-Houguan of Minjiang river. Efforts have been made to explore new route of studying shoal evolution in water conservancy discipline, it is expect to have a bright future in practical application.
第一部分以RS技术为手段，建立闽江竹岐至侯官河段遥感信息与水深之间的数学模型。研究表明，用最低通航设计水位时的水域边界裁取研究水域，可消除边界点因水陆信息混合产生的误差，提高遥感水深精度。
第二部分对人工神经网络理论进行了简要概括，对BP网络的原理进行了分析。在分析影响河道浅滩演变因素的基础上，提出了基于BP神经网络的河道浅滩演变预测模型，分析并确定了模型的输入、输出因子，提出各因子的获取方法以及训练样本选取方法，并对BP网络设计进行了探讨。以闽江竹岐至侯官河段为实例，计算结果表明，模型预测结果与实际值吻合良好。这为河道浅滩演变预测研究提供了一种新方法。
第三部分对GIS与平面二维泥沙数学模型集成意义、问题和方法进行了分析。在此基础上，建立了基于GIS的泥沙数学模型，设计了两种模式数据交换的接口程序，探讨了泥沙模型计算域空间离散问题。最后成功地对闽江竹岐至侯官河段进行了整治工程效果预测，所得结果被航道部门采用。
在第四部分的研究中，以VB和GIS为开发工具，针对闽江竹岐至侯官河段研究中的二种模型，集成开发了浅滩演变分析的模拟与预测系统，设计了系统的总体结构，探讨了系统功能和系统关键技术的实现。
本文各章不仅进行了理论研究，同时还结合交通部人材基金项目和闽江水口坝下航道整治项目和闽江航道信息管理系统项目进行了应用研究。本文的研究是对水利学科中浅滩演变预测研究的一次新探索，且具有很好的应用前景。
Studying on river shoal evolution is a fundamental work in the science of water conservancy, water conservancy projects and waterways planning, designing, management and engineering feasibility. In this paper, river shoal evolution is studied by means of modern science and technique, combined with the real projects. Particular contents are presented as follow.
In Part I , the mathematical model between remote sensing image spectral value and survey water-depth is built in Zhuqi-Houguan of Minjiang river by remote sensing (RS). It is proved that the error caused by mixing water-land information on boundary may be eliminated by choosing the research waters within the water boundary under designed lowest navigable stage, and the precision of remote water-depth of river may be enhanced.
In Part II, the theory of artificial neural network (ANN) is introduced briefly, the principle of back propagation(BP) neural network is analyzed. River shoal evolution prediction models on a BP neural network are established on analyzing factors affecting shoal evolution in a river, and input as well as output factors are determined by analyzing, the methods of obtaining these factors and selecting training samples are presented, and the designing of a BP network is also studied. The predicted result showed good agreement with field data in Zhouqi-Houguan of Minjiang river.
In Part III, the significance, problem and methods of integrating plane 2-D sediment mathematical model with geographical information system (GIS) are discussed . The mathematical model based on GIS is built, and the interface program of data conversion between the two models is designed, and the spatial discretion of the computational domain is discussed. The model is used to predict the influence of regulation work on shoal evolution in Zhouqi-Houguan of Minjiang river, and the results are adopted by the department of responsibility conservancy.
In Part IV, the system of simulating and predicting is developed by mean of a Visual Basic and GIS ,according to the two shoal evolution prediction models in Zhouqi-Houguan of Minjiang river. The general framework is designed, the schemes of some critical techniques of the platform such as data interface and model-creating techniques are presented, then the main functions and platform are outlined.
The work in this paper is concerned with the theoretical method, combined with the projects of regulation work of waterway and management information system in Zhouqi-Houguan of Minjiang river. Efforts have been made to explore new route of studying shoal evolution in water conservancy discipline, it is expect to have a bright future in practical application.
引文
1．钱宁，张仁，周明德，河床演变学，科学出版社，1989
2．Kobus H 编著，模型试验的理论与方法，清华大学出版社，1988
3．李昌华，河工模型试验，人民交通出版社，1981
4．窦国仁，全沙河工模型试验的研究，科学通报，1981，14
5．左东启，模型试验的理论与方法，水利电力出版社，1984
6．汤立群，唐洪武，陈国祥，河海大学泥沙研究进展及成果综述，1999，(6)：29-32
7. Preissmann, A., Propagation des intumescenses dans les canaux et rivers, First Congress of the French Association for Computation, Grenoble, 1996.
8. Belleudy, P., Rahuel, J-L. And Yang Guolu, CARICHAR-Mobile bed modeling of graded sediment in unsteady flow, AIRH Congress, 1987.
9. Cunge, J. A., and Perdreau, N., Mobile bed fluvial mathematical models, La Houiile Blanche, 1973
10. Cunge, J. A., and Simons, D. B., Mathematical model of unsteady flow in mobile bed rivers with alluvial channel resistance, 16th IAHR Congress, 1975
11．韩其为，何明民，水库淤积与河床演变的(一维)数学模型，泥沙研究，1987，(3)：14-29
12．张丽春，方红卫，府仁寿，一维非均匀泥沙数学模型，泥沙研究，1998，(3)：81-85
13．梁国亭，高懿堂，梁跃平，非恒定流泥沙数学模型原理及应用，1999，(4)：44-4
14. Leenderts, J. J., Liu, S. K., Three Dimensional flow simulation in estuaries, Proc. Int. Symp. Unsteady Flow in open Cannels, Int. Assoc. Hydraul. Res. Newcastle-upon-type Eng., 1976,11-23
15. Thomposon, J. F., Numerical solution of flow problem using body fitted coordinate system. In: Computation Fluid Dynamics. Hemisphere Publishing Corp., 1980:183-256
16．刘子龙，王船海，长江口三维水流模拟，河海大学学报，1996(5)：108-110
17. Heaps, N. S., On the numerical solution of the three dimensional hydrodynamic equations for tides and storm surges, Men. Soc. R. Sci. Liég, Vol. 2,1972,143-180
18. T amai M, Ikeya T. Tree-dimensional flow over alternating point bars in meandering channel. J. Hydr Engrg, 1985,3(1):1-3
19. Sarraf S, Kahawita R, Eljabi N. 3-D general movable mesh in water circulation. J Comp in Civ. Engrg, ASCE, 1988,2(2): 170-187
20. Shimizu Y, Yamaguchi H, Itakura T. Tree-dimensional computation of flow and bed deformation. J Hydr Engrg, ASCE, 1991,116(9): 1090-1108
21. Sommeijer B P, Kok J. Implementation and performance of the time-integration of a 3D numerical transport model. Intermational Journal for Numerical Methods in Fluids, 1995,21(4):349-367
22. Lin Bingliang, Roger A Falconer. Numerical modeling of three dimensional suspend sediment for estuarine and coastal waters. Journal of Hydraulic Research, 1996,34(4):435-456
23．曹祖德，王桂芬．三维潮流、波浪、泥沙数值模拟，两岸港口及海岸开发研计会论文集，1993，87-93
24．丁平兴，等．波-流共同作用下的三维悬沙扩散方程，科学通报，1999，44(12)：1339-1341
25. Van Rijn, L. C., Mathematical modeling of suspended sediment in non-uniform flows. J. Hydraul. Engrg., ASCE, 110(12), 1733-1754
26. Rahuel, J. L., Holly, F. M., Belleudy, P. J., and Yang, G., Modeling of riverbed evolution for bedload sediment mixtures[J]. J. Hydr. Engrg.,ASCE, 115(1), 1521-1542
27. Jose l. Lopez and Marco A. Falcon, Calculation of bed change in mountain stream[J], J. Hydraulic Engrg.,1999,125(3):263-270
28. Struiksma N. Bed deformation in curved alluvial channels. J Hydr Res, 1985,23(1):57-79
29. Han Z C, Cheng H P. 2-dimensional sediment mathematical model for Hangzhou Bay. Proc 3rd Intern Symp. on River Sedimentation. The Univ. of Missisiisppi ,USA, March 31～April 4, 1986:463-471
30. Lin B N, Han Z C, Sun H B et al. Two-D simulation of sediment transport and bed detbrmation by tides. Proc 3rd Intern Syrup on River Sedimentation. The Univ. of Missisiisppi ,USA, March 31～April 4, 1986:388-399
31. Holly, EM. Jr and Rahuel J. L. Numerical physical framework for mobile-bed modeling. J. Hydraulic Research, 1990,28(4):401-416
32. Einstein, tt.A, The Bed Load Function for Sediment Transportation in Open Channel Flow, U.S., Dept. Agri. Tech. Bull. 1026,1950,
33. Englund, F. And Hansen, E., A monograph on sediment transportation in alluvial streams, Teknisk, Forlag Copenhagen, 1972
34．何少芩，林炳南，破开算子法在二维潮流中的应用，海洋学报，1984，(2)
35．窦国仁等，河道二维全沙数学模型的研究，水利水运科学研究，1987，(2)：1-11
36．吴伟明，一维、二维及嵌套泥沙数学模型的研究与应用[学位论文]，武汉水利电力大学，1991，9
37．韩其为，等．三峡水库二维泥沙数学模型研究，长江三峡工程泥沙与航运关键技术研究专题报告，武汉工业大学出版社，1993
38．李东风，张红武，许雨新等，黄河下游平面二维水沙运动模拟的有限法，泥沙研究，1999，(4)：59-63
39. Nico Struksma, Prediction of 2-D Bed Topography in Rivers, J. of Hydraulic Eng.,1985,111(8): 1169-1182
40. Pavlovic, R.N., Two-Dimensional Depth-Average Model for the Calculation of Sediment Transport and River Bed Deformation, 2Nd Inter. Sympo. On Refined Flow Modeling and Turbulence Measurement, U.S.A.,19985
41. Tingsanchali, T., Rodi, W., Depth Average Calculation of Suspended Sediment Transport in Rivers,3rd Inter. Sympo. on River Sed.,1986
42. Larock, B.E., Turbulent Transport Models in River Sedimentation,3rd. Inter. Sympo. on River Sed., 1986
43. Sheng, Y.P., Second-order closure modeling of turbulent flow and sediment in coastal and estuarine waters, 3rd . Inter. Sympo. on river Sed., 1986
44. Lu Yongjun, Chen Guoxiang, A new 2-D sediment mathematical model, River
Sedimentation Theory and Applications, 1999:783-788
45. Goldberg, D. E., and Wylie, E. B.: Characteristics method using the time-line interpolations, ASCE, 1983,109(5)
46. Leendertse J J, A water quality simulation model for well-mixed estuaries and coastal seas, Principles of Computation, Tile Rand Corporation RM-6230,1970
47. Yanenko N N. One the difference method of calculation of multidimensional heal conduction equation (Russian). Dokl. Aked. Nauk. USSR, 1950,128(5)
48. Benque J. P., ET AL., Engineering application of computational hydraulics, Pitman Co., 1982,2
49. Patankar S.V. Numerical heat transfer and fluid flow. Hemsphero Publishing Co. Washingdn D. C., 1980
50. Vieux, B. E., Bralts, V. E, Segerlind, L. J. and Wallace, R. B., Finite element watershed modeling :one-dimensional elements, J. Water Resour. Plan. Manage., 1990,116(6),803-819
51. T. Tuceiarelli and D. Termini, Finite-Element modeling of floodplain flow[J], J. of Hydraulic Engrg.,2000,126(6):416-424
52. Herrera, I., Boundary methods in water resources, Adv. Water Resources,5(9), 1982
53. White, W.R., Mill, H. And Crabbe, A.D. Sediment Transport Theories: A Review, Proc. Inst. Civil Engrs., Vol. 59 Pt2, 1975, 265-292
54. Yang, C.T., sediment Transport and Unit Stream Power, To be Published in Handbook of Civil Engineering by Technomic Publishing, 1987
55．何明民，韩其为，挟沙能力级配及有效床沙级配的确定，水利学报，1990，(3)：1-12
56．刘青泉，回流区泥沙起动规律及回流饱和挟沙力．全国泥沙基本理论研究学术讨论会论文集，1992，94-101
57. Feldman, A. D., HEC models for water resources system simulation: Theory and Experience, The Hydraulic Engineering Center, Davis, California, 1981
58. Barkham, D.E. and Dawdy, D.R., Resistance equation for alluvial chalmel flow, J. of Hydraulic. Eng., 1986, 102(10), 1479-1489
59. David G. Rhodes and Alastair K. Senior, Numerical study of resistance with rib roughness of various scales, J. of Hydraulic. Eng.,2000,126(7):541-546
60．张修忠，王光谦，河道及河口一维及二维嵌套泥沙数学模型，水利学报，2001，(10)：82-87
61．常福田，航道整治，人民交通出版社，1995
62．罗保平，动态设计思想在界牌航道整治设计中的应用及有关问题探讨，航道工程与维护，2001：4-8
63. Sorensen H R et al. Application of GIS in hydrological and hydraulic modeling :DLIS and MIKEⅡ-GIS in HydroGIS 96:Application of Geographical information systems in Hydrology and water resource manager. IAHS Pub.,1996,235:149-156
64. Leggett D J, Jones A. The application of GIS for flood defense in the Anglican region:developing for the future[J].Int. 7 of Geographical Information Systems ,1996,10(1): 103-116
65. Sui D Z. GIS and urban studies: positivism, post-positivism, and beyond[J]. Urban Geography, 1994,15(3):258～278
66. Mejia-Navarro M, Carcia L A. Natural hazard and risk assessment using decision support systems, application :Glenwood Springs, Colorado[J], Environmental & Engineering Geoscience, 1996, 2(3): 299-324
67. Carrara A, et al. GIS techniques and statistical model in evaluating landslide hazard[J]. Earth Surface Processes and Landforms ,1991,16: 427-445
68. Burrough P A., Environmental modeling with geographical information system[A],In:Kemp Z(ed.),Innovations in GIS4[C], London: Taylor & Francis Ltd., 1997, 143-153
69. Wheeler D J. Linking Environmental models with geographic information systems for global change research. Photogrammetric Engineering & Remote Sensing, 1993,59(10): 1497-1501
70. Hallam C A, Lanfear K J, Salisbury J M et al. Geographic information system (GIS) and image processing for storm-water management modeling using XPSWMM in
Tallahassee, Florida[A], in: Proceedings awra Annual Symposium 98[C], GIS and Water Resource, 1998,305～313
71. Me]ia-Navarro M, Carcia L A. Natural hazard and risk assessment using decision support systems, application :Glenwood Springs, Colorado [J], Environmental & Engineering Geoscience, 1996, 2(3): 299-324
72. Burrough P A., Environmental modeling with geographical information system[A],In: Kemp Z(ed.),Innovations in GIS4[C], London: Taylor & Francis Ltd., 1997, 143-153
73. Wheeler D J. Linking Enviromnental models with geographic information systems for global change research. Photogrammetric Engineering & Remote Sensing, 1993,59(10):1497-1501
74. Carrara A, et al. GIS techniques and statistical model in evaluating landslide hazard [J]. Earth Surface Processes and Landforms, 1991,16:427-445
75. FRASER A S and HODGSON K. Outline of an environmental information system. Environmental Monitor Assess[J],1995,36:207-216
76. Sui D Z. GIS-Based urban modeling :Practices, Problems, and Prospects, International Journal of Geographical Information Science, 1998,12(7):651-671
77. Hiscock K M ,et al. Groundwater vulnerability assessment: two case studies using GIS methodology [J].Quarterly Journal of Engineering Geology, 1995,28:179-194
78．戴福初，等．城市建设用地与地质环境协调评价的GIS方法及其应用[J]，地球科学，2000，25(2)：209-214
79．徐富春，等．GIS—IMS在重点流域环境管理中的应用[J]，环境科学动态，2000，(1)：16-18
80．何庆成．RS和GIS技术集成及其在黄河三角洲海岸带环境变迁研究中的应用，中国地质大学博士论文，1998
81．王礼育，罗丹，从遥感图像看珠江口门规划治理效果，人民珠江，2000，(3)：43-47
82．范作江，遥感与地理信息系统相结合的城市扩展研究，遥感信息，1997，(3)：12-16
83．高志强，等．基于RS和GIS的中国土地资源生态环境质量同人口分布的关系研
究．遥感学报，1999，(1)：66-70
84. Shenk W E, Curian R J., The detection of dust storms over land and water with satellite visible and infrared measurement, Mon. Wean Rev., 1974,102:820-837
85. D Stranski, R A Reynolds, M Kahru, et al., Estimation of particulate organic carbon in the ocean from satellite remote sensing, Science, 1999,285:239-242
86. Casacchia, F. Mazzarrini, Salvatorl, R., Salvini., Rock-type discrimination by field, TM and SPORT data, TARN FLAT, Antarctica, Int. J. Remote Sensing,1999,20(2):403-420
87. Carpenter D J., Modeling inland water quality using landsat data, Remote Sensing of Environment,1983,13:345-352
88. A. K. Saraf, P. R. Choudhary, B. Sarma and P. Ghosh, Cover impacts of reservoirs on groundwater and vegetable: a study based on remote sensing and GIS techniques, Int. J. Remote Sensing, 2001,22(13):2439-2448
89. Matteson W. Hiland et al. Change analysis and spatial information management for coastal environments, Microstation Manager, Mar, 1993,51-58
90．邱颖，孟庆武，李悌，神经网络用于岩性及岩相预测的可行性分析，地球物理进展，2001，16(3)：78-83
91．昌培印，宋玉普，基于人工神经网络的混凝土疲劳寿命估算，海洋工程，2001，19(3)：72-76
92．应行仁，曾南，采用BP神经网络记忆模糊规则的控制．自动化学报，1991，17(1)：63-67
93．沙保卫，夏元友，三峡二期工程砼温控问题的人工神经网络研究，长江科学院院报，2001，18(4)：26-28
94. Knanina,E. D. A Simple Procedure for Pruning Back-Propagation Trained Neural Networks. IEEE Trans. On Neural Networks. 1990,1(2):239-242
95. X Y, XIE Y M AND ZHU R G. An engineering geology evaluation method based artificial neural network and its application. Int. J. Eng. Geol., 1997,47(1-2): 149-156.
96. Brown, M., and Harris, C. J., Neurofuzzy Adaptive Modeling and Control, Hemel Hempstead, V. K.:Prentice Hall,1997
97. Fuchsia K., A Neural Networks for Visual Pattern Recognition, Neural Networks, edited by Clifford Lau, IEEE Press,1992:222-232
98. Widrow B.,30 Years of Adaptive Neural Networks: Perceptron, Madaline, and Backpropagtion, Proceedings of the IEEE,Vol.78,No.9:27-53,SEPT.1990
99. T. Yabuta and T. Yamada, Learning control using neural networks. In Proc. IEEE Int. Conf. Robot. Automat., Sacramento, CA. 1991,4:740-745
100. Trent R, Molinas A, Gagarin N. An artificial neural network for computing sediment transport. In: Shen H W, Su S T, Wen F. Hydraulic Engineering'93, Proc. Of the 1993 Conference. ASC
101. Li Rong and Li Yitian. Applied Researches of Neural Network in Flood Prediction. International. Journal of Sediment Research, No. 2,1999
102. N. Karunanithi,et al. Neural Networks for River Flow Prediction. J. of Computer Civil Engineering. 1994,8(2):201-220
103. Campolo,M., Andreussi, P., and Soldati, A. River Flood Forecasting with a Neural Network Model. Water Resources Research, 1999,35(4): 1191-1197
104. Zealand, C. M., Barn, D. H., and Simonovic, S. P. Short Term Stream flow Forecasting using Artificial Neural Network. Journal of Hydrology, 1999,214:32-48
105. Polcyn F C. The measurement of water depth by remote sensing techniques. The University of Michigan, Institute and Technology, Willow Run Laboratories, 1970,10, 8973-26
106. Brown W L. Polcyn F C, Stewartt S E. A method for calculation water depth, attenuation coefficients and bottom reflectance characteristics. Proceeding of the Seventh International Symposium on Remote Sensing of Environment. 1971,663-682
107. I. Helmings. A historical overiew of radar imagery of sea bottom topography. International Journal of Remote Sensing, 1998,19:1447-1454
108. W. Alpers,I. Hennings. A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar. Journal of Geophysical Research, 1984,89:10529-10546
109. J. Vogelzang. The mapping of bottom topography with imaging radar: a comparison
of hydrodynamic modulation in some existing models. International Journal of Remote Sensing, 1989,10:1503-1518
110. Bierwirth, P.N.et al. Shallow sea-floor reflectance and water depth derived by unmixing multispectral imagery. Photogrammetric Engineering & Remote Sensing, 1993.3,331-338
111．黄韦艮，傅斌，周长宝等，星载SAR水下地形和水深遥感的最佳雷达系统参数模拟[J]，遥感学报，2000，4(3)：172-177
112．王国兴，SPOT卫星资料在水深信息中应用研究，河海大学学报[J]，1998，(6)
113．张鹰，张东，水深遥感方法研究，河海大学学报，1998，(6)
114．尤玉明，汉江航道整治中水深遥感技术应用研究，第八届全国海岸工程学术讨论会论文集，海洋出版社，1997
115．张永生，遥感图像信息系统，科学出版社，2000
116．徐冠华，田国良，王超等．遥感信息科学的进展和展望．地理学报，1996，51(5)：385-397
117．李铜基，张兆瑛．海洋航空遥感一体化测量技术．海洋技术，1998，17(1)：1-8
118．胡著智，王慧麟，陈钦峦，遥感技术与地学应用，南京大学出版社，1999
119．郑新奇等，基于RS与GIS的区域生态环境质量综合评价研究——以山东为例，环境科学学报，2000，20(4)：489-493
120．刘正军，基于GIS与遥感集成的土地利用现状动态监测，遥感信息，2000，1，29-31
121．何延波，遥感(RS)利地理信息系统(GIS)在水文模型中的应用—以普定寨河流域为例，中国科学院地球化学研究所博士论文，1998
122．陈一梅，张东生，卫星遥感在港口、航道工程中的应用回顾与展望，水运工程，2001，(10)：10-13
123．何青，恽才兴，遥感在海岸岸滩稳定分析中的应用，海洋学报，1999，(5)：87-93
124．张东生，张鹰，灌河口河口演变的遥感图象解译，河海大学学报，1991，(4)：18-26
125．许祥向，遥感技术在珠江口治理规划中应用研究，人民珠江，1996，(6)：17-19
126．林敏基，海洋与海岸带遥感应用，北京，海洋出版社，1991
127．丁贤荣，张鹰，王文，同相水深—辐射关系率定，河海大学学报，1998，(6)
128．黄永葛，陈一梅，李奕琼，闽江水口坝下航道工程泥沙数学模型的应用研究，福建省航道局，2001
129．孙家权，舒宁，关泽群，遥感原理、方法与应用，测绘出版社，1997
130．任成，朱重光，郑柯等，TM图像的SOMP几何纠正法．遥感学报，2001，5(4)：295-299
131．华瑞林，遥感制图，南京大学出版社，1990
132. Lyzenga D R. Shallow-water reflectance modeling with application to remote sensing of the ocean floor. Proc of 13th International Symposium on Remote Sensing of Environment. Vol. 1,April 1979,583-602.
133. Tanis F J. Evaluation of Landsat-The math mapper Data for shallow water bathymetry. Proc of 18th International Symposium on Remote Sensing Environment. 1984
134．钟瑚穗，过达．GIS和水深遥感在海岸工程冲淤分析中的应用．水利水运科学研究，2000，(3)：43-47
135．王永骥，徐健．神经元网络控制，机械工业出版社，1998
136．丛爽，面向MATLAB工具箱的神经网络理论与应用，中国科学技术大学出版社，1998
137．戴葵，神经网络实现技术，国防科技大学出版社，1998
138．徐海亮，河口网河区水文相关模拟的人工神经网络方法与应用，人民珠江，1999，(3)：15-18
139．陈一梅，水利枢纽下游最低通航水位推算方法研究，东南大学学报，2002，(2)
140．彭清娥，刘兴年，曹叔尤，流域年均含沙量的人工神经网络模型，水利学报，2001，(11)：79-83
141．F．G．罗巴，使用人工神经网络预报河道流量，水利水电快报，2001，22(1)：30-33
142. Li Yitian. Gan Minghui and Li Rong. Sediment Deposition and Flood Disaster in Dongting Lake.Proceedings of the Seventh Internatinal Symposium on River
Sedimentation, 1999
143．张小峰，许全喜，裴莹，流域产流产沙BP网络预报模型的初步研究，水科学进展，2001，12(1)：17-22
144．魏海坤，徐嗣鑫，宋文忠，神经网络的泛化理论和泛化方法，自动化学报，2001，27(11)：806-815
145. Baum E B, Haussler D. What Size Net Gives Valid Generalization ?.NIPS 1,1989,San Mateo,CA:81-90
146．周毅，徐柏龄，神经网络中的正交设计法研究，南京大学学报，2001，37(1)：72-78
147. Foody J G M,Arora M K. An Evaluation of Some Factors Affecting the Accuracy of Classification by an Artificial Neural Network. International Journal or Remote Sensing, 1997,18:799-810
148. Sungzoon Cho, Yongjung Cho,Sungchul Yoon. Reliable Roll Force Prediction in Cold Mill Using Multiple Neural Networks. IEEE Trans on Neural Networks, 1997,8(4):874-882
149. Erol Gelenbe, Zhi-Hong Mao,Yan-Da Li. Function Approximation with Spiked Random Networks. IEEE Trans on Neural Networks, 1999,10(1):3-8
150. Lippmann R P. An Introduction to Computing with Neural Nets. IEEE ASSP Magazine, 1987,2:4-22
151. Kanellopoulos I, Wilkinson G G. Strategies and Best Practice for Neural Network Image Classification. INT J. Remote Sensing, 1997,18(4):711-725
152．骆剑承，周成虎，杨艳，人工神经网络遥感影像分类模型及其与知识集成方法研究，遥感学报，2001，5(2)：122-129
153. Mirchadani G, Cao W. On Hidden Units in Neural Nets. IEEE Trans Circuits Syst, 1989,36(15):661-664
154. Kolen J F, Pollack J B. Back Propagation is Sensitive to Initial Conditions. NIPS 3, 1991,San Mateo, CA:860-867
155. Schmidt W F, Raudys S, Kraaijveld M A et al. Initialization, back-propagation and generalization of feed-forward classifiers. In:Proc. IEEE Int. Conf. Neural
Networks, 1993,598-604
156. Baldi P. Temporal Evolution Generalization during Learning in Linear Networks. Neural Computation,1991,(3):589-603
157. Chauvin Y. Generalization Dynamics in LMS Trained Linear Networks .NIPS 3,1991,San Mateo,CA:890-896
158. Hoskins J C, Himmelblau D M. Process Control ia Artificial Neural Networks and Reinforcement Learning. Comput Chem Eng, 1992,16(4): 141-151
159．陈一梅，王震，张东生，闽江竹岐至侯官河段河床演变规律与整治初探[J]，东南大学学报，2001，3，79-84
160．王协康，方铎，曹叔尤，推移质输沙率神经网络模型的试验研究[J]，水利学报，2000，9，74-78
161．陈一梅，水运工程试验检测概论，人民交通出版社，2000
162. Pandya A S, Macy R B. Pattern Recognition with Neural Network in C++. IEEE Press(中译本)，电子工业出版社，1999
163. Segee B E. Using spectral techniques for improved performance in ANN. Proc IEEE, 1993,500-505
164. Lee S, Kil R M. A Gaussian potential funct on network with hierarchnically self-organizing learning. Neural Networks, 199,4,207-224
165. Wu Y S. A new approach to design a simplest ANN for performing certain specific problem. In: Proceedings of the International Conference on Neural Information Processing, Beijing, 1995,477-480
166. Wu Youshou, Zhao Mingsheng, Ding Xiaoqing. A new perceptron model with tunable activation function. Chinese Journal of Ele(?)ronics, 1996,5(2),55-62
167. Hornik K. Approximation capabilities of multilayer feedforward networks. Neural Networks, 1991,4,251-257
168．吴佑寿，赵明生，丁晓青，一种激活函数可调的新人工神经网络及应用，中国科学，E辑，1997，27(1)：55-60
169. Lippmann R P. An Introduction to computing with neural nets[J]. IEEE. ASSP Magazine, 1987,2,4～22
原图像不清晰
170. Kanellopoulos I, Wilkinson G G. Strategies and Best Practice for Neural Network Image Classification. INT. J. Remote Sensing, 1997,18(4):711-725
171．边馥苓，GIS地理信息系统原理和方法[M]，测绘出版社，1996
172．王基国，概述当代GIS技术特点[M]，中国科学技术文库，科学技术出版社，1998
173．郑立中，抓住机遇促进应用推动我国地理信息系统产业发展[J]，遥感信息，1996
174．刘亚岚，遥感与GIS支持下的基于网络的洪涝灾害监测评估系统关键技术研究[J]，遥感学报，2001，(1)：53-57
175．徐冠华，遥感信息科学的进展和展望，地理学报[J]，1996，5，385-397
176．张东生，蒋勤，江苏北部灌河口悬沙输送数学模型[J]，海洋学报，1991，13(1)：125-136
177．窦国仁等，河道二维全沙数学模型的研究[J]，水利水运科学研究，1987：1-11
178. Abel,D.J., Kilby, P.J., Davis, H.J.R, The System Integration Problem. INT. J. Geographical Information System, 1994,8(1): 1-2
179. Ding, Y., and Fotheringham, A. S., The Integration of Spatial Snalysis and GIS. Computer, Enviromnent and Urban System, 1992,16:3-9
180. Devantier B A, Feldman A D. Review of GIS Application in Hydrologic Modeling. Journal of Water Resources Planning and Management. Proceeding of the American Society of Civil Engineering 1993,119:246-261
181. Jain S K, Chowdhary H, Seth S M, Nema R K. Flood estimation using a GIUH based on a conceptual rainfall-runoff model and GIS. ITC Journal 1997, 1:20-25
182. Maidment D R. GIS and hydrologic modeling-An assessment of progress[A]. In Environmental Modeling with GIS[C]. edited by M F Goodchild, B Parks, L Steyaert(Oxford University Press) 1993,35-50
183. Jonathan Harris et al.. Goodchild M F et al. eds.. Integrated Use of a GIS and Tree-Dimensional, Finite-Element Model: San Gabriel Basin Groundwater Flow Analyses. Environmental Modeling with GIS. Oxford University Press, 1993:168-172
184. Goodchild M F. The state of GIS for environmental problem-solving[A]. In Environmental Modeling with GIS edited by M F Goodchild[C]. B O Parks L T
Steyaert(New York:Oxford University Press) 1993
185. LIAO Hsiuhua, Tim U S. An interactive modeling environment for Non-point source pollution control. Journal of the American Water Resources Association, 1997,33(3):591-603
186. Burrough P A. Environmental modeling with geographical information system[A]. In: Kemp Z(ed.). Innovations in GIS4[C]. London: Taylor & Francis Ltd., 1997.143-153
187．李志林，朱庆，数字高程模型[M]，武汉测绘科技大学出版社，2000
188．陈一梅，沙质海岸河口航道回淤计算方法及其应用，河海大学学报，2000，28(6)：82-86
189．谢鉴衡等，河流模拟[M]，水利电力出版社，1989：121-139
190．罗云启，罗毅，数字化地理信息系统MapInfo应用大全，北京希望电子出版社，2001，9
191．Francesco Balenna著，翔实翻译组译，Visual Basic6编程技术大全，机械工业出版社，2000，6
2．Kobus H 编著，模型试验的理论与方法，清华大学出版社，1988
3．李昌华，河工模型试验，人民交通出版社，1981
4．窦国仁，全沙河工模型试验的研究，科学通报，1981，14
5．左东启，模型试验的理论与方法，水利电力出版社，1984
6．汤立群，唐洪武，陈国祥，河海大学泥沙研究进展及成果综述，1999，(6)：29-32
7. Preissmann, A., Propagation des intumescenses dans les canaux et rivers, First Congress of the French Association for Computation, Grenoble, 1996.
8. Belleudy, P., Rahuel, J-L. And Yang Guolu, CARICHAR-Mobile bed modeling of graded sediment in unsteady flow, AIRH Congress, 1987.
9. Cunge, J. A., and Perdreau, N., Mobile bed fluvial mathematical models, La Houiile Blanche, 1973
10. Cunge, J. A., and Simons, D. B., Mathematical model of unsteady flow in mobile bed rivers with alluvial channel resistance, 16th IAHR Congress, 1975
11．韩其为，何明民，水库淤积与河床演变的(一维)数学模型，泥沙研究，1987，(3)：14-29
12．张丽春，方红卫，府仁寿，一维非均匀泥沙数学模型，泥沙研究，1998，(3)：81-85
13．梁国亭，高懿堂，梁跃平，非恒定流泥沙数学模型原理及应用，1999，(4)：44-4
14. Leenderts, J. J., Liu, S. K., Three Dimensional flow simulation in estuaries, Proc. Int. Symp. Unsteady Flow in open Cannels, Int. Assoc. Hydraul. Res. Newcastle-upon-type Eng., 1976,11-23
15. Thomposon, J. F., Numerical solution of flow problem using body fitted coordinate system. In: Computation Fluid Dynamics. Hemisphere Publishing Corp., 1980:183-256
16．刘子龙，王船海，长江口三维水流模拟，河海大学学报，1996(5)：108-110
17. Heaps, N. S., On the numerical solution of the three dimensional hydrodynamic equations for tides and storm surges, Men. Soc. R. Sci. Liég, Vol. 2,1972,143-180
18. T amai M, Ikeya T. Tree-dimensional flow over alternating point bars in meandering channel. J. Hydr Engrg, 1985,3(1):1-3
19. Sarraf S, Kahawita R, Eljabi N. 3-D general movable mesh in water circulation. J Comp in Civ. Engrg, ASCE, 1988,2(2): 170-187
20. Shimizu Y, Yamaguchi H, Itakura T. Tree-dimensional computation of flow and bed deformation. J Hydr Engrg, ASCE, 1991,116(9): 1090-1108
21. Sommeijer B P, Kok J. Implementation and performance of the time-integration of a 3D numerical transport model. Intermational Journal for Numerical Methods in Fluids, 1995,21(4):349-367
22. Lin Bingliang, Roger A Falconer. Numerical modeling of three dimensional suspend sediment for estuarine and coastal waters. Journal of Hydraulic Research, 1996,34(4):435-456
23．曹祖德，王桂芬．三维潮流、波浪、泥沙数值模拟，两岸港口及海岸开发研计会论文集，1993，87-93
24．丁平兴，等．波-流共同作用下的三维悬沙扩散方程，科学通报，1999，44(12)：1339-1341
25. Van Rijn, L. C., Mathematical modeling of suspended sediment in non-uniform flows. J. Hydraul. Engrg., ASCE, 110(12), 1733-1754
26. Rahuel, J. L., Holly, F. M., Belleudy, P. J., and Yang, G., Modeling of riverbed evolution for bedload sediment mixtures[J]. J. Hydr. Engrg.,ASCE, 115(1), 1521-1542
27. Jose l. Lopez and Marco A. Falcon, Calculation of bed change in mountain stream[J], J. Hydraulic Engrg.,1999,125(3):263-270
28. Struiksma N. Bed deformation in curved alluvial channels. J Hydr Res, 1985,23(1):57-79
29. Han Z C, Cheng H P. 2-dimensional sediment mathematical model for Hangzhou Bay. Proc 3rd Intern Symp. on River Sedimentation. The Univ. of Missisiisppi ,USA, March 31～April 4, 1986:463-471
30. Lin B N, Han Z C, Sun H B et al. Two-D simulation of sediment transport and bed detbrmation by tides. Proc 3rd Intern Syrup on River Sedimentation. The Univ. of Missisiisppi ,USA, March 31～April 4, 1986:388-399
31. Holly, EM. Jr and Rahuel J. L. Numerical physical framework for mobile-bed modeling. J. Hydraulic Research, 1990,28(4):401-416
32. Einstein, tt.A, The Bed Load Function for Sediment Transportation in Open Channel Flow, U.S., Dept. Agri. Tech. Bull. 1026,1950,
33. Englund, F. And Hansen, E., A monograph on sediment transportation in alluvial streams, Teknisk, Forlag Copenhagen, 1972
34．何少芩，林炳南，破开算子法在二维潮流中的应用，海洋学报，1984，(2)
35．窦国仁等，河道二维全沙数学模型的研究，水利水运科学研究，1987，(2)：1-11
36．吴伟明，一维、二维及嵌套泥沙数学模型的研究与应用[学位论文]，武汉水利电力大学，1991，9
37．韩其为，等．三峡水库二维泥沙数学模型研究，长江三峡工程泥沙与航运关键技术研究专题报告，武汉工业大学出版社，1993
38．李东风，张红武，许雨新等，黄河下游平面二维水沙运动模拟的有限法，泥沙研究，1999，(4)：59-63
39. Nico Struksma, Prediction of 2-D Bed Topography in Rivers, J. of Hydraulic Eng.,1985,111(8): 1169-1182
40. Pavlovic, R.N., Two-Dimensional Depth-Average Model for the Calculation of Sediment Transport and River Bed Deformation, 2Nd Inter. Sympo. On Refined Flow Modeling and Turbulence Measurement, U.S.A.,19985
41. Tingsanchali, T., Rodi, W., Depth Average Calculation of Suspended Sediment Transport in Rivers,3rd Inter. Sympo. on River Sed.,1986
42. Larock, B.E., Turbulent Transport Models in River Sedimentation,3rd. Inter. Sympo. on River Sed., 1986
43. Sheng, Y.P., Second-order closure modeling of turbulent flow and sediment in coastal and estuarine waters, 3rd . Inter. Sympo. on river Sed., 1986
44. Lu Yongjun, Chen Guoxiang, A new 2-D sediment mathematical model, River
Sedimentation Theory and Applications, 1999:783-788
45. Goldberg, D. E., and Wylie, E. B.: Characteristics method using the time-line interpolations, ASCE, 1983,109(5)
46. Leendertse J J, A water quality simulation model for well-mixed estuaries and coastal seas, Principles of Computation, Tile Rand Corporation RM-6230,1970
47. Yanenko N N. One the difference method of calculation of multidimensional heal conduction equation (Russian). Dokl. Aked. Nauk. USSR, 1950,128(5)
48. Benque J. P., ET AL., Engineering application of computational hydraulics, Pitman Co., 1982,2
49. Patankar S.V. Numerical heat transfer and fluid flow. Hemsphero Publishing Co. Washingdn D. C., 1980
50. Vieux, B. E., Bralts, V. E, Segerlind, L. J. and Wallace, R. B., Finite element watershed modeling :one-dimensional elements, J. Water Resour. Plan. Manage., 1990,116(6),803-819
51. T. Tuceiarelli and D. Termini, Finite-Element modeling of floodplain flow[J], J. of Hydraulic Engrg.,2000,126(6):416-424
52. Herrera, I., Boundary methods in water resources, Adv. Water Resources,5(9), 1982
53. White, W.R., Mill, H. And Crabbe, A.D. Sediment Transport Theories: A Review, Proc. Inst. Civil Engrs., Vol. 59 Pt2, 1975, 265-292
54. Yang, C.T., sediment Transport and Unit Stream Power, To be Published in Handbook of Civil Engineering by Technomic Publishing, 1987
55．何明民，韩其为，挟沙能力级配及有效床沙级配的确定，水利学报，1990，(3)：1-12
56．刘青泉，回流区泥沙起动规律及回流饱和挟沙力．全国泥沙基本理论研究学术讨论会论文集，1992，94-101
57. Feldman, A. D., HEC models for water resources system simulation: Theory and Experience, The Hydraulic Engineering Center, Davis, California, 1981
58. Barkham, D.E. and Dawdy, D.R., Resistance equation for alluvial chalmel flow, J. of Hydraulic. Eng., 1986, 102(10), 1479-1489
59. David G. Rhodes and Alastair K. Senior, Numerical study of resistance with rib roughness of various scales, J. of Hydraulic. Eng.,2000,126(7):541-546
60．张修忠，王光谦，河道及河口一维及二维嵌套泥沙数学模型，水利学报，2001，(10)：82-87
61．常福田，航道整治，人民交通出版社，1995
62．罗保平，动态设计思想在界牌航道整治设计中的应用及有关问题探讨，航道工程与维护，2001：4-8
63. Sorensen H R et al. Application of GIS in hydrological and hydraulic modeling :DLIS and MIKEⅡ-GIS in HydroGIS 96:Application of Geographical information systems in Hydrology and water resource manager. IAHS Pub.,1996,235:149-156
64. Leggett D J, Jones A. The application of GIS for flood defense in the Anglican region:developing for the future[J].Int. 7 of Geographical Information Systems ,1996,10(1): 103-116
65. Sui D Z. GIS and urban studies: positivism, post-positivism, and beyond[J]. Urban Geography, 1994,15(3):258～278
66. Mejia-Navarro M, Carcia L A. Natural hazard and risk assessment using decision support systems, application :Glenwood Springs, Colorado[J], Environmental & Engineering Geoscience, 1996, 2(3): 299-324
67. Carrara A, et al. GIS techniques and statistical model in evaluating landslide hazard[J]. Earth Surface Processes and Landforms ,1991,16: 427-445
68. Burrough P A., Environmental modeling with geographical information system[A],In:Kemp Z(ed.),Innovations in GIS4[C], London: Taylor & Francis Ltd., 1997, 143-153
69. Wheeler D J. Linking Environmental models with geographic information systems for global change research. Photogrammetric Engineering & Remote Sensing, 1993,59(10): 1497-1501
70. Hallam C A, Lanfear K J, Salisbury J M et al. Geographic information system (GIS) and image processing for storm-water management modeling using XPSWMM in
Tallahassee, Florida[A], in: Proceedings awra Annual Symposium 98[C], GIS and Water Resource, 1998,305～313
71. Me]ia-Navarro M, Carcia L A. Natural hazard and risk assessment using decision support systems, application :Glenwood Springs, Colorado [J], Environmental & Engineering Geoscience, 1996, 2(3): 299-324
72. Burrough P A., Environmental modeling with geographical information system[A],In: Kemp Z(ed.),Innovations in GIS4[C], London: Taylor & Francis Ltd., 1997, 143-153
73. Wheeler D J. Linking Enviromnental models with geographic information systems for global change research. Photogrammetric Engineering & Remote Sensing, 1993,59(10):1497-1501
74. Carrara A, et al. GIS techniques and statistical model in evaluating landslide hazard [J]. Earth Surface Processes and Landforms, 1991,16:427-445
75. FRASER A S and HODGSON K. Outline of an environmental information system. Environmental Monitor Assess[J],1995,36:207-216
76. Sui D Z. GIS-Based urban modeling :Practices, Problems, and Prospects, International Journal of Geographical Information Science, 1998,12(7):651-671
77. Hiscock K M ,et al. Groundwater vulnerability assessment: two case studies using GIS methodology [J].Quarterly Journal of Engineering Geology, 1995,28:179-194
78．戴福初，等．城市建设用地与地质环境协调评价的GIS方法及其应用[J]，地球科学，2000，25(2)：209-214
79．徐富春，等．GIS—IMS在重点流域环境管理中的应用[J]，环境科学动态，2000，(1)：16-18
80．何庆成．RS和GIS技术集成及其在黄河三角洲海岸带环境变迁研究中的应用，中国地质大学博士论文，1998
81．王礼育，罗丹，从遥感图像看珠江口门规划治理效果，人民珠江，2000，(3)：43-47
82．范作江，遥感与地理信息系统相结合的城市扩展研究，遥感信息，1997，(3)：12-16
83．高志强，等．基于RS和GIS的中国土地资源生态环境质量同人口分布的关系研
究．遥感学报，1999，(1)：66-70
84. Shenk W E, Curian R J., The detection of dust storms over land and water with satellite visible and infrared measurement, Mon. Wean Rev., 1974,102:820-837
85. D Stranski, R A Reynolds, M Kahru, et al., Estimation of particulate organic carbon in the ocean from satellite remote sensing, Science, 1999,285:239-242
86. Casacchia, F. Mazzarrini, Salvatorl, R., Salvini., Rock-type discrimination by field, TM and SPORT data, TARN FLAT, Antarctica, Int. J. Remote Sensing,1999,20(2):403-420
87. Carpenter D J., Modeling inland water quality using landsat data, Remote Sensing of Environment,1983,13:345-352
88. A. K. Saraf, P. R. Choudhary, B. Sarma and P. Ghosh, Cover impacts of reservoirs on groundwater and vegetable: a study based on remote sensing and GIS techniques, Int. J. Remote Sensing, 2001,22(13):2439-2448
89. Matteson W. Hiland et al. Change analysis and spatial information management for coastal environments, Microstation Manager, Mar, 1993,51-58
90．邱颖，孟庆武，李悌，神经网络用于岩性及岩相预测的可行性分析，地球物理进展，2001，16(3)：78-83
91．昌培印，宋玉普，基于人工神经网络的混凝土疲劳寿命估算，海洋工程，2001，19(3)：72-76
92．应行仁，曾南，采用BP神经网络记忆模糊规则的控制．自动化学报，1991，17(1)：63-67
93．沙保卫，夏元友，三峡二期工程砼温控问题的人工神经网络研究，长江科学院院报，2001，18(4)：26-28
94. Knanina,E. D. A Simple Procedure for Pruning Back-Propagation Trained Neural Networks. IEEE Trans. On Neural Networks. 1990,1(2):239-242
95. X Y, XIE Y M AND ZHU R G. An engineering geology evaluation method based artificial neural network and its application. Int. J. Eng. Geol., 1997,47(1-2): 149-156.
96. Brown, M., and Harris, C. J., Neurofuzzy Adaptive Modeling and Control, Hemel Hempstead, V. K.:Prentice Hall,1997
97. Fuchsia K., A Neural Networks for Visual Pattern Recognition, Neural Networks, edited by Clifford Lau, IEEE Press,1992:222-232
98. Widrow B.,30 Years of Adaptive Neural Networks: Perceptron, Madaline, and Backpropagtion, Proceedings of the IEEE,Vol.78,No.9:27-53,SEPT.1990
99. T. Yabuta and T. Yamada, Learning control using neural networks. In Proc. IEEE Int. Conf. Robot. Automat., Sacramento, CA. 1991,4:740-745
100. Trent R, Molinas A, Gagarin N. An artificial neural network for computing sediment transport. In: Shen H W, Su S T, Wen F. Hydraulic Engineering'93, Proc. Of the 1993 Conference. ASC
101. Li Rong and Li Yitian. Applied Researches of Neural Network in Flood Prediction. International. Journal of Sediment Research, No. 2,1999
102. N. Karunanithi,et al. Neural Networks for River Flow Prediction. J. of Computer Civil Engineering. 1994,8(2):201-220
103. Campolo,M., Andreussi, P., and Soldati, A. River Flood Forecasting with a Neural Network Model. Water Resources Research, 1999,35(4): 1191-1197
104. Zealand, C. M., Barn, D. H., and Simonovic, S. P. Short Term Stream flow Forecasting using Artificial Neural Network. Journal of Hydrology, 1999,214:32-48
105. Polcyn F C. The measurement of water depth by remote sensing techniques. The University of Michigan, Institute and Technology, Willow Run Laboratories, 1970,10, 8973-26
106. Brown W L. Polcyn F C, Stewartt S E. A method for calculation water depth, attenuation coefficients and bottom reflectance characteristics. Proceeding of the Seventh International Symposium on Remote Sensing of Environment. 1971,663-682
107. I. Helmings. A historical overiew of radar imagery of sea bottom topography. International Journal of Remote Sensing, 1998,19:1447-1454
108. W. Alpers,I. Hennings. A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar. Journal of Geophysical Research, 1984,89:10529-10546
109. J. Vogelzang. The mapping of bottom topography with imaging radar: a comparison
of hydrodynamic modulation in some existing models. International Journal of Remote Sensing, 1989,10:1503-1518
110. Bierwirth, P.N.et al. Shallow sea-floor reflectance and water depth derived by unmixing multispectral imagery. Photogrammetric Engineering & Remote Sensing, 1993.3,331-338
111．黄韦艮，傅斌，周长宝等，星载SAR水下地形和水深遥感的最佳雷达系统参数模拟[J]，遥感学报，2000，4(3)：172-177
112．王国兴，SPOT卫星资料在水深信息中应用研究，河海大学学报[J]，1998，(6)
113．张鹰，张东，水深遥感方法研究，河海大学学报，1998，(6)
114．尤玉明，汉江航道整治中水深遥感技术应用研究，第八届全国海岸工程学术讨论会论文集，海洋出版社，1997
115．张永生，遥感图像信息系统，科学出版社，2000
116．徐冠华，田国良，王超等．遥感信息科学的进展和展望．地理学报，1996，51(5)：385-397
117．李铜基，张兆瑛．海洋航空遥感一体化测量技术．海洋技术，1998，17(1)：1-8
118．胡著智，王慧麟，陈钦峦，遥感技术与地学应用，南京大学出版社，1999
119．郑新奇等，基于RS与GIS的区域生态环境质量综合评价研究——以山东为例，环境科学学报，2000，20(4)：489-493
120．刘正军，基于GIS与遥感集成的土地利用现状动态监测，遥感信息，2000，1，29-31
121．何延波，遥感(RS)利地理信息系统(GIS)在水文模型中的应用—以普定寨河流域为例，中国科学院地球化学研究所博士论文，1998
122．陈一梅，张东生，卫星遥感在港口、航道工程中的应用回顾与展望，水运工程，2001，(10)：10-13
123．何青，恽才兴，遥感在海岸岸滩稳定分析中的应用，海洋学报，1999，(5)：87-93
124．张东生，张鹰，灌河口河口演变的遥感图象解译，河海大学学报，1991，(4)：18-26
125．许祥向，遥感技术在珠江口治理规划中应用研究，人民珠江，1996，(6)：17-19
126．林敏基，海洋与海岸带遥感应用，北京，海洋出版社，1991
127．丁贤荣，张鹰，王文，同相水深—辐射关系率定，河海大学学报，1998，(6)
128．黄永葛，陈一梅，李奕琼，闽江水口坝下航道工程泥沙数学模型的应用研究，福建省航道局，2001
129．孙家权，舒宁，关泽群，遥感原理、方法与应用，测绘出版社，1997
130．任成，朱重光，郑柯等，TM图像的SOMP几何纠正法．遥感学报，2001，5(4)：295-299
131．华瑞林，遥感制图，南京大学出版社，1990
132. Lyzenga D R. Shallow-water reflectance modeling with application to remote sensing of the ocean floor. Proc of 13th International Symposium on Remote Sensing of Environment. Vol. 1,April 1979,583-602.
133. Tanis F J. Evaluation of Landsat-The math mapper Data for shallow water bathymetry. Proc of 18th International Symposium on Remote Sensing Environment. 1984
134．钟瑚穗，过达．GIS和水深遥感在海岸工程冲淤分析中的应用．水利水运科学研究，2000，(3)：43-47
135．王永骥，徐健．神经元网络控制，机械工业出版社，1998
136．丛爽，面向MATLAB工具箱的神经网络理论与应用，中国科学技术大学出版社，1998
137．戴葵，神经网络实现技术，国防科技大学出版社，1998
138．徐海亮，河口网河区水文相关模拟的人工神经网络方法与应用，人民珠江，1999，(3)：15-18
139．陈一梅，水利枢纽下游最低通航水位推算方法研究，东南大学学报，2002，(2)
140．彭清娥，刘兴年，曹叔尤，流域年均含沙量的人工神经网络模型，水利学报，2001，(11)：79-83
141．F．G．罗巴，使用人工神经网络预报河道流量，水利水电快报，2001，22(1)：30-33
142. Li Yitian. Gan Minghui and Li Rong. Sediment Deposition and Flood Disaster in Dongting Lake.Proceedings of the Seventh Internatinal Symposium on River
Sedimentation, 1999
143．张小峰，许全喜，裴莹，流域产流产沙BP网络预报模型的初步研究，水科学进展，2001，12(1)：17-22
144．魏海坤，徐嗣鑫，宋文忠，神经网络的泛化理论和泛化方法，自动化学报，2001，27(11)：806-815
145. Baum E B, Haussler D. What Size Net Gives Valid Generalization ?.NIPS 1,1989,San Mateo,CA:81-90
146．周毅，徐柏龄，神经网络中的正交设计法研究，南京大学学报，2001，37(1)：72-78
147. Foody J G M,Arora M K. An Evaluation of Some Factors Affecting the Accuracy of Classification by an Artificial Neural Network. International Journal or Remote Sensing, 1997,18:799-810
148. Sungzoon Cho, Yongjung Cho,Sungchul Yoon. Reliable Roll Force Prediction in Cold Mill Using Multiple Neural Networks. IEEE Trans on Neural Networks, 1997,8(4):874-882
149. Erol Gelenbe, Zhi-Hong Mao,Yan-Da Li. Function Approximation with Spiked Random Networks. IEEE Trans on Neural Networks, 1999,10(1):3-8
150. Lippmann R P. An Introduction to Computing with Neural Nets. IEEE ASSP Magazine, 1987,2:4-22
151. Kanellopoulos I, Wilkinson G G. Strategies and Best Practice for Neural Network Image Classification. INT J. Remote Sensing, 1997,18(4):711-725
152．骆剑承，周成虎，杨艳，人工神经网络遥感影像分类模型及其与知识集成方法研究，遥感学报，2001，5(2)：122-129
153. Mirchadani G, Cao W. On Hidden Units in Neural Nets. IEEE Trans Circuits Syst, 1989,36(15):661-664
154. Kolen J F, Pollack J B. Back Propagation is Sensitive to Initial Conditions. NIPS 3, 1991,San Mateo, CA:860-867
155. Schmidt W F, Raudys S, Kraaijveld M A et al. Initialization, back-propagation and generalization of feed-forward classifiers. In:Proc. IEEE Int. Conf. Neural
Networks, 1993,598-604
156. Baldi P. Temporal Evolution Generalization during Learning in Linear Networks. Neural Computation,1991,(3):589-603
157. Chauvin Y. Generalization Dynamics in LMS Trained Linear Networks .NIPS 3,1991,San Mateo,CA:890-896
158. Hoskins J C, Himmelblau D M. Process Control ia Artificial Neural Networks and Reinforcement Learning. Comput Chem Eng, 1992,16(4): 141-151
159．陈一梅，王震，张东生，闽江竹岐至侯官河段河床演变规律与整治初探[J]，东南大学学报，2001，3，79-84
160．王协康，方铎，曹叔尤，推移质输沙率神经网络模型的试验研究[J]，水利学报，2000，9，74-78
161．陈一梅，水运工程试验检测概论，人民交通出版社，2000
162. Pandya A S, Macy R B. Pattern Recognition with Neural Network in C++. IEEE Press(中译本)，电子工业出版社，1999
163. Segee B E. Using spectral techniques for improved performance in ANN. Proc IEEE, 1993,500-505
164. Lee S, Kil R M. A Gaussian potential funct on network with hierarchnically self-organizing learning. Neural Networks, 199,4,207-224
165. Wu Y S. A new approach to design a simplest ANN for performing certain specific problem. In: Proceedings of the International Conference on Neural Information Processing, Beijing, 1995,477-480
166. Wu Youshou, Zhao Mingsheng, Ding Xiaoqing. A new perceptron model with tunable activation function. Chinese Journal of Ele(?)ronics, 1996,5(2),55-62
167. Hornik K. Approximation capabilities of multilayer feedforward networks. Neural Networks, 1991,4,251-257
168．吴佑寿，赵明生，丁晓青，一种激活函数可调的新人工神经网络及应用，中国科学，E辑，1997，27(1)：55-60
169. Lippmann R P. An Introduction to computing with neural nets[J]. IEEE. ASSP Magazine, 1987,2,4～22
原图像不清晰
170. Kanellopoulos I, Wilkinson G G. Strategies and Best Practice for Neural Network Image Classification. INT. J. Remote Sensing, 1997,18(4):711-725
171．边馥苓，GIS地理信息系统原理和方法[M]，测绘出版社，1996
172．王基国，概述当代GIS技术特点[M]，中国科学技术文库，科学技术出版社，1998
173．郑立中，抓住机遇促进应用推动我国地理信息系统产业发展[J]，遥感信息，1996
174．刘亚岚，遥感与GIS支持下的基于网络的洪涝灾害监测评估系统关键技术研究[J]，遥感学报，2001，(1)：53-57
175．徐冠华，遥感信息科学的进展和展望，地理学报[J]，1996，5，385-397
176．张东生，蒋勤，江苏北部灌河口悬沙输送数学模型[J]，海洋学报，1991，13(1)：125-136
177．窦国仁等，河道二维全沙数学模型的研究[J]，水利水运科学研究，1987：1-11
178. Abel,D.J., Kilby, P.J., Davis, H.J.R, The System Integration Problem. INT. J. Geographical Information System, 1994,8(1): 1-2
179. Ding, Y., and Fotheringham, A. S., The Integration of Spatial Snalysis and GIS. Computer, Enviromnent and Urban System, 1992,16:3-9
180. Devantier B A, Feldman A D. Review of GIS Application in Hydrologic Modeling. Journal of Water Resources Planning and Management. Proceeding of the American Society of Civil Engineering 1993,119:246-261
181. Jain S K, Chowdhary H, Seth S M, Nema R K. Flood estimation using a GIUH based on a conceptual rainfall-runoff model and GIS. ITC Journal 1997, 1:20-25
182. Maidment D R. GIS and hydrologic modeling-An assessment of progress[A]. In Environmental Modeling with GIS[C]. edited by M F Goodchild, B Parks, L Steyaert(Oxford University Press) 1993,35-50
183. Jonathan Harris et al.. Goodchild M F et al. eds.. Integrated Use of a GIS and Tree-Dimensional, Finite-Element Model: San Gabriel Basin Groundwater Flow Analyses. Environmental Modeling with GIS. Oxford University Press, 1993:168-172
184. Goodchild M F. The state of GIS for environmental problem-solving[A]. In Environmental Modeling with GIS edited by M F Goodchild[C]. B O Parks L T
Steyaert(New York:Oxford University Press) 1993
185. LIAO Hsiuhua, Tim U S. An interactive modeling environment for Non-point source pollution control. Journal of the American Water Resources Association, 1997,33(3):591-603
186. Burrough P A. Environmental modeling with geographical information system[A]. In: Kemp Z(ed.). Innovations in GIS4[C]. London: Taylor & Francis Ltd., 1997.143-153
187．李志林，朱庆，数字高程模型[M]，武汉测绘科技大学出版社，2000
188．陈一梅，沙质海岸河口航道回淤计算方法及其应用，河海大学学报，2000，28(6)：82-86
189．谢鉴衡等，河流模拟[M]，水利电力出版社，1989：121-139
190．罗云启，罗毅，数字化地理信息系统MapInfo应用大全，北京希望电子出版社，2001，9
191．Francesco Balenna著，翔实翻译组译，Visual Basic6编程技术大全，机械工业出版社，2000，6