基于模糊Petri网的瓦斯突出空间预测模型研究
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摘要
煤与瓦斯突出是严重影响煤矿安全生产的自然灾害之一,依据瓦斯突出机理因素、因素权重和时空序列,引入模糊Petri网和工作流挖掘技术,描述瓦斯突出的动态演变过程,进而用于瓦斯突出预测的推理分析,可为突出预测研究、突出前兆动态信息的处理及应用提供一种新的理论方法和技术途径。本文在对瓦斯突出预测方法和模糊Petri网理论深入研究的基础上,实地调研分析瓦斯突出的空间分布,提出模糊Petri网的瓦斯突出预测模型,分别从瓦斯突出的模糊Petri空间建模、体系结构、模糊空间Petri网的规则描述和动态推理、模型系统的实现等几个方面进行深入和系统的研究。
提出了瓦斯突出的模糊Petri网空间模型,针对瓦斯突出各因素空间分布的特点,解决了瓦斯突出的模糊性描述和空间建模问题。在深入分析Petri网和模糊Petri网相关定义、模型结构、空间关联动态性质和模糊知识表示的基础上,研究了模糊Petri网和瓦斯突出的空间预测的结合点；深入研究瓦斯突出的模糊空间表示,扩展模糊Petri网的相关组件成分,建立瓦斯突出的模糊Petri网空间模型,使瓦斯突出影响因素在不同的空间位置通过空间模型表示出来。
提出了基于工作流网的瓦斯突出空间数据挖掘,实现了瓦斯突出空间状态因素和业务流程建模的统一,解决瓦斯突出空间模型的可实现性和空间决策问题。在论证空间数据挖掘和工作流结合的必要性和可行性基础上,分析工作流及过程优化,研究了基于Petri网的工作流网,从定义、组件和Petri网进行工作流建模的优点等几方面进行了对比分析；通过扩展工作流参考模型的接口,提出了基于工作流网的空间数据挖掘体系结构,进一步结合瓦斯突出的空间预测研究,建立瓦斯突出工作流网模型,将瓦斯突出空间预测模型作为工作流过程定义模型,挖掘瓦斯突出预测的规则,用于瓦斯突出预测的过程；从静态数据挖掘和动态数据额挖掘两个方面,在对关键技术实现研究的基础上,完成了实例分析,突破了模糊Petri网的瓦斯突出模型的可实现性瓶颈,建立了模型系统的体系结构。
提出了模糊空间Petri网,为增强模糊Petri网空间描述的通用性,将空间属性作为重要指标,解决了瓦斯突出不同空间状态建模的动态关联和推理等可实现性问题,从定义、组件、知识表示、规则描述和动态推理等方面形成了较为完整的空间建模理论体系。深入研究空间位置和模糊Petri网的结合,引入空间关联因子,借鉴相关扩展的模糊Petri网,给出了模糊空间Petri网的定义；依据空间影响因子分布情况,详细地阐述了状态关联影响组件、变迁关联影响组件、状态关联多值阈值的构成及含义,解决了瓦斯突出不同空间区域关联的知识表示问题；随后,对比基本Petri网结构进行了等价性分析,对比基本模糊Petri网进行了改进性分析；深入地研究了模糊空间Petri网的知识表示,详细描述了相关分层的思想、面向对象表示和XML表示；最后,详细研究了动态推理和模糊空间Petri网规则描述,提出了一种带反馈的动态推理算法。
深入探索Petri网的可实现性,建立基于WF的瓦斯突出预测模型系统,解决了瓦斯突出Petri网建模的程序可实现性。基于微软最新工作流开发平台WF4.0,实现了基本Petri网和模糊空间Petri网的建模和组件开发。在此基础上建立了模型验证系统,可以描述模糊Petri网的规则推理和动态测试。
该论文有图72幅,表10个,参考文献157篇。
Coal and gas outburst presented obviously space-time and multidimensional complexity, describing dynamic evolvement process was used to infer and analyze the gas outburst according to gas outburst mechanism factor, factor weight and space-time sequence. Fuzzy Petri net spatial forecast modeling of gas outburst was presented, which thoroughly and systemically researched fuzzy Petri net model, architecture, rule description and dynamic inference of fuzzy spatial Petri net, realization of model system.
Fuzzy Petri net spatial model of gas outburst was presented according to space distribution character of outburst diversified factor, and fuzzy description and spatial model of gas outburst were solved. The integration of fuzzy Petri net and gas outburst spatial forecast was researched. The component of fuzzy Petri net was extended integrating with space distribution character of outburst diversified factor. Lucubrating Fuzzy spatial representation of gas outburst, effect factor of gas outburst was represented by spatial model in the different spatial place.
Spatial data mining of gas outburst based on workflow net was presented in order to realize the unification between spatial state factor and business flow modeling of gas outburst and to solve spatial model realization and spatial decision question. Workflow net based on Petri net was researched and spatial data mining architecture based on workflow net was presented by extending workflow reference model. Workflow net model of gas outburst was built combing with spatial forecast of gas outburst and key technology realization was analyzed from static and dynamic data mining.
Fuzzy spatial Petri net was presented convenient for describing spatial dynamic association and dynamic reasoning and enhancing spatial describing universality of fuzzy Petri net. Gas outburst knowledge representation of different spatial distribution association was solved according to spatial effect factor distribution, which structures and meanings of state association effect component, transition association effect component and state association multi-valued threshold were illuminated in detailed. Knowledge representation of fuzzy spatial Petri net was researched in detailed and a dynamic reasoning algorithm with feedback was presented.
Model System of gas outburst based on WF was built based on probing deeply into Petri net realizability, and program realizability of Petri net modeling for gas outburst was solved. Modeling and developing component of basic Petri net and fuzzy spatial Petri net were implemented based on Microsoft workflow foundation 4.0, and model verification system was built which could described rule reasoning and dynamic testing of fuzzy Petri net.
提出了瓦斯突出的模糊Petri网空间模型,针对瓦斯突出各因素空间分布的特点,解决了瓦斯突出的模糊性描述和空间建模问题。在深入分析Petri网和模糊Petri网相关定义、模型结构、空间关联动态性质和模糊知识表示的基础上,研究了模糊Petri网和瓦斯突出的空间预测的结合点；深入研究瓦斯突出的模糊空间表示,扩展模糊Petri网的相关组件成分,建立瓦斯突出的模糊Petri网空间模型,使瓦斯突出影响因素在不同的空间位置通过空间模型表示出来。
提出了基于工作流网的瓦斯突出空间数据挖掘,实现了瓦斯突出空间状态因素和业务流程建模的统一,解决瓦斯突出空间模型的可实现性和空间决策问题。在论证空间数据挖掘和工作流结合的必要性和可行性基础上,分析工作流及过程优化,研究了基于Petri网的工作流网,从定义、组件和Petri网进行工作流建模的优点等几方面进行了对比分析；通过扩展工作流参考模型的接口,提出了基于工作流网的空间数据挖掘体系结构,进一步结合瓦斯突出的空间预测研究,建立瓦斯突出工作流网模型,将瓦斯突出空间预测模型作为工作流过程定义模型,挖掘瓦斯突出预测的规则,用于瓦斯突出预测的过程；从静态数据挖掘和动态数据额挖掘两个方面,在对关键技术实现研究的基础上,完成了实例分析,突破了模糊Petri网的瓦斯突出模型的可实现性瓶颈,建立了模型系统的体系结构。
提出了模糊空间Petri网,为增强模糊Petri网空间描述的通用性,将空间属性作为重要指标,解决了瓦斯突出不同空间状态建模的动态关联和推理等可实现性问题,从定义、组件、知识表示、规则描述和动态推理等方面形成了较为完整的空间建模理论体系。深入研究空间位置和模糊Petri网的结合,引入空间关联因子,借鉴相关扩展的模糊Petri网,给出了模糊空间Petri网的定义；依据空间影响因子分布情况,详细地阐述了状态关联影响组件、变迁关联影响组件、状态关联多值阈值的构成及含义,解决了瓦斯突出不同空间区域关联的知识表示问题；随后,对比基本Petri网结构进行了等价性分析,对比基本模糊Petri网进行了改进性分析；深入地研究了模糊空间Petri网的知识表示,详细描述了相关分层的思想、面向对象表示和XML表示；最后,详细研究了动态推理和模糊空间Petri网规则描述,提出了一种带反馈的动态推理算法。
深入探索Petri网的可实现性,建立基于WF的瓦斯突出预测模型系统,解决了瓦斯突出Petri网建模的程序可实现性。基于微软最新工作流开发平台WF4.0,实现了基本Petri网和模糊空间Petri网的建模和组件开发。在此基础上建立了模型验证系统,可以描述模糊Petri网的规则推理和动态测试。
该论文有图72幅,表10个,参考文献157篇。
Coal and gas outburst presented obviously space-time and multidimensional complexity, describing dynamic evolvement process was used to infer and analyze the gas outburst according to gas outburst mechanism factor, factor weight and space-time sequence. Fuzzy Petri net spatial forecast modeling of gas outburst was presented, which thoroughly and systemically researched fuzzy Petri net model, architecture, rule description and dynamic inference of fuzzy spatial Petri net, realization of model system.
Fuzzy Petri net spatial model of gas outburst was presented according to space distribution character of outburst diversified factor, and fuzzy description and spatial model of gas outburst were solved. The integration of fuzzy Petri net and gas outburst spatial forecast was researched. The component of fuzzy Petri net was extended integrating with space distribution character of outburst diversified factor. Lucubrating Fuzzy spatial representation of gas outburst, effect factor of gas outburst was represented by spatial model in the different spatial place.
Spatial data mining of gas outburst based on workflow net was presented in order to realize the unification between spatial state factor and business flow modeling of gas outburst and to solve spatial model realization and spatial decision question. Workflow net based on Petri net was researched and spatial data mining architecture based on workflow net was presented by extending workflow reference model. Workflow net model of gas outburst was built combing with spatial forecast of gas outburst and key technology realization was analyzed from static and dynamic data mining.
Fuzzy spatial Petri net was presented convenient for describing spatial dynamic association and dynamic reasoning and enhancing spatial describing universality of fuzzy Petri net. Gas outburst knowledge representation of different spatial distribution association was solved according to spatial effect factor distribution, which structures and meanings of state association effect component, transition association effect component and state association multi-valued threshold were illuminated in detailed. Knowledge representation of fuzzy spatial Petri net was researched in detailed and a dynamic reasoning algorithm with feedback was presented.
Model System of gas outburst based on WF was built based on probing deeply into Petri net realizability, and program realizability of Petri net modeling for gas outburst was solved. Modeling and developing component of basic Petri net and fuzzy spatial Petri net were implemented based on Microsoft workflow foundation 4.0, and model verification system was built which could described rule reasoning and dynamic testing of fuzzy Petri net.
引文
[1]俞启香.矿井瓦斯防治[M].徐州：中国矿业大学出版社,1992.
[2]于不凡,白帆,刘明.煤矿瓦斯防治技术[M].北京：中国经济出版社.1987.
[3]中华人民共和国煤炭工业部.防治煤与瓦斯突出细则[M].北京：煤炭工业出版社,1995.
[4]程伟.煤与瓦斯突出危险性预测及防治技术[M].徐州：中国矿业大学,2003.
[5]聂百胜,何学秋,王恩元等.煤与瓦斯突出预测技术研究现状及发展趋势[J].中国安全科学学报,2003,13(6)：4043.
[6]漆旺生,凌标灿,蔡嗣经.煤与瓦斯突出预测研究动态及展望[J].中国安全科学学报,2003,13(12)：14.
[7]Wang Kai, et al. A Prediction Model for the Risk of Coal and Gas Outburst Based on Artificial Neural Network[C]. Coal Mine Safety and Health:Proceedings of the International Mining Technology'98 Symposium. Beijing:China Coal Industry Publishing House,1998:51-56
[8]俞善炳,谈庆明,丁雁生等.含气多孔介质卸压层裂的间隔特征—突出的前兆[J].力学学报,1998,30(2)：145150.
[9]苏文叔.利用瓦斯涌出动态指标预测煤与瓦斯突出[C].防治煤与瓦斯突出论文集.北京：中国煤炭工业劳动保护科学技术学会,2001.
[10]S.M. Chen, J.S. Ke, J.F. Chang, Knowledge representation using fuzzy Petri nets[J].IEEE Trans. Knowledge Data Engrg,1990,2 (3):311-319.
[11]袁崇义.Petri网原理与应用[M].北京：电子工业出版社,2005.
[12]何新贵.模糊知识处理的理论与技术[M].北京：国防工业出版社,1999.
[13]吴哲辉.Petri网导论[M].北京：机械工业出版社,2006.
[14]何新贵.模糊Petri网[J].计算机学报,1994,17(12)：946950.
[15]X. Li, F. Lara-Rosano.Adaptive fuzzy petri nets for dynamic knowledge representation and inference[J].Expert Systems with Applications,2000 (19):235-241.
[16]高艳忠,蒋承林.模糊(Fuzzy)数学在煤与瓦斯突出预测中的应用[J].江西煤炭科技,2006,2(2)：68.
[17]吴海清.模糊数学在预测煤与瓦斯突出中的应用[J].陕西煤炭技术,1992(4)：1618.
[18]陈凤,申东日等.模糊小波网络在煤与瓦斯突出预测中的应用[J].煤矿安全,2006(10)：5154.
[19]金芳勇,石必明.模糊综合评判在煤与瓦斯突出监测中的应用[J].江西煤炭科技,2006,1(1)：1012.
[20]章壮新,吴桂义.煤与瓦斯突出模糊专家系统[J].贵州工业大学学报,2001,30(3)：21-24.
[21]桂祥友,郁钟铭.基于模糊聚类关联分析法的煤与瓦斯突出程度分析[J].安全与环境学报,2006,6(4)：85-88.
[22]吴财芳,曾勇,张子戌等.基于模糊神经网络的煤与瓦斯突出区域预测研究[J].煤田地质与勘探,2002,30(6)：4-8.
[23]秦书玉.煤与瓦斯突出预报的模糊聚类相似分析法[J].中国地质灾害与防治学报,2003,14(4)：58-61.
[24]张子戌,刘高峰,吕闰生.基于模糊模式识别的煤与瓦斯突出区域预测[J].煤炭学报,2007,32(6)：592-595.
[25]李德仁,王树良,史文中等.论空间数据挖掘和知识发现[J].武汉大学学报信息科学版,2001,26(6)：491-499.
[26]孙庆先,方涛,郭达志.空间数据挖掘技术中的区划效应及在矿山中的应用[J].煤炭学报,2007,(32)8：804-807.
[27]张光建,王立杰,汪文生.用空间数据挖掘技术提升煤矿安全管理水平[J].煤矿安全,2005(7)：51-53.
[28]王凯,王轶波,卢杰.煤与瓦斯突出动态前兆的非线性特征研究[J].采矿与安全工程学报,2007,24(1)：22-24.
[29]李成武.区域煤与瓦斯突出危险性动态评价方法[J].煤矿安全,2007(5)：64-66.
[30]毛善君,郑升飞.煤和瓦斯的动态预测[J].煤田地质与勘探,1992,20(2)：36-39.
[31]章立清,秦玉金,姜文忠等.我国矿井瓦斯涌出量预测方法研究现状及展望[J].煤矿安全,2007,393(8)：58-60.
[32]张耀平,叶青,贾真真,江文武.工作面瓦斯涌出量预测及瓦斯来源分析[J].中国矿业,2007,11(16)：46-52.
[33]魏建平,龙威成,刘明举,王根卿.鹤壁八矿瓦斯赋存规律及其主要控制因素分析[J].煤矿安全,2007(5)：61-63.
[34]王以功,林晓霞,杨晓东,戴仁竹.基于工作流的煤矿安全信息管理系统建模[J].中国矿业,2007,11(16)：43-45.
[35]邱进伟,张国枢.基于模糊优选的矿井通风系统决策研究[J].煤矿安全,2007(4)：1-4.
[36]李飒.基于数据仓库的煤矿安全信息管理系统设计[J].煤矿安全,2007(2)：60-62.
[37]刘泽宇.矿井瓦斯安全智能巡检系统在古书院矿的应用[J].煤矿安全,2007(5)：58-60.
[38]王恩营.利用瓦斯涌出量计算瓦斯含量的方法及可靠性评价[J].煤矿开采,2007(12)：1-2.
[39]殷秋朝,张小东.利用瓦斯涌出量计算瓦斯含量的方法在大平矿的实践[J].煤矿安全,2007,(9)：19-22.
[40]易伟欣.爆层瓦斯含量晌地质要素分析及预测[J].中州煤炭,2007(1)：71-73.
[41]李成武.煤与瓦斯突出危险性灰色分类方法实验研究[J].煤矿安全,2007(6)：1-4.
[42]赵旭生.“低指标突出现象”原因分析及防范对策[J].煤矿安全,2007(5)：67-69.
[43]别玉平,高军伟,魏风清.长虹公司二煤层煤与瓦斯突出危险性区域预测[J].中州煤炭,2007(4)：80-82.
[44]张连成,张建民.超前钻释放瓦斯防治严重突出危险煤层煤与瓦斯突出[J].煤矿安全,2007(6)：58-60.
[45]刘明举,牟全斌,魏建平等.新安煤矿瓦斯赋存规律及影响因素探讨[J].煤矿安全,2007(11)：60-62.
[46]陈胜利.徐州矿区瓦斯涌出规律探讨[J].煤炭科技,2007(4)：77-79.
[47]王清亮.智能决策理论在矿井通风系统中的应用研究[J].煤矿安全,2007(4)：5-8.
[48]于不凡,王佑安.煤矿瓦斯灾害防治及利用技术手册[M].北京：煤炭工业出版社,2000.
[49]张子戌,袁崇孚.瓦斯地质数学模型方法[J].煤炭学报,1999,24(4)：8-12.
[50]秦汝祥.煤与瓦斯突出预报研究现状综述[J].能源技术与管理,2005(1)：7-9.
[51]A.J. Bugarin, S. Barro. Fuzzy reasoning supported by Petri nets[J]. IEEE Trans. Fuzzy Systems,1994(2):135-150.
[52]T. Cao, A.C. Sanderson, Task sequence planning using fuzzy Petri nets [J]. IEEE Trans. Systems Man Cybernet,1995,25 (5):755-769.
[53]J. Cardoso, R. Valette, D. Dubois. Petri nets with uncertain markings, in:G. Rozenberg (Ed.),Advances in Petri Nets, Lecture Notes in Computer Science, Springer-Verlag, New York, 1990:65-78.
[54]Andreu, D., Pascal, J.,& Valette, R. Fuzzy Petri net-based programmable logic controller [J]. IEEE Transactions on SMC—Part B:Cybernetics,1997(27):952-961.
[55]Hanna, M. M., Buck, A.,& Smith, R. Fuzzy Petri nets with neural networks to model products quality from a CNC-milling machining centre [J]. IEEE Transactions on SMC, Part A: Systems and Humans,1996(26):638-645.
[56]M.L. Garg, S.I. Ashon, P.V. Gupta. A fuzzy Petri net for knowledge representation and reasoning[J]. Inform. Process. Lett,1991(39):165-171.
[57]T. Cao, A.C. Sanderson. A fuzzy Petri net approach to reasoning about uncertainty in Robotic systems, in:Proc. IEEE Int. Conf. Robotics and Automation,1993:317-322.
[58]Scarpelli, H.,& Gomide, F. A high-level fuzzy net approach for discovering potential inconsistencies in fuzzy knowledge bases [J]. Fuzzy Sets and Systems,1994(64):175-193.
[59]A. Konar, A.K. Mandal, Uncertainty management in expert systems using fuzzy Petri nets,IEEE Ttrans[J]. Knowledge Data Engrg,1996,8(1):96-105.
[60]Scarpelli, H.,& Gomide, F. Fuzzy reasoning and fuzzy Petri nets in manufacturing systems modeling[J]. Journal of Intelligent Fuzzy Systems,1993(1):225-241.
[61]C.G. Looney, Fuzzy Petri nets for rule-based decision making [J]. IEEE Trans. Systems Man Cybernet,1988,18 (1):178-183.
[62]Tang, R., Pang, G. K. H.,& Woo, S. S. A continuous fuzzy Petri net tool for intelligent process monitoring and control [J]. IEEE Transactions on Control System Technology, 1995(3):318-329.
[63]Yeung, D. S.,& Tsang, E. C. C. Fuzzy knowledge representation and reasoning using Petri nets[J]. Expert System Application,1994 (7):281-290
[64]W. Pedrycz. A fuzzy cognitive structure for pattern recognition [J]. Pattern Recognition Lett, 1989(9):305-313.
[65]Witold Pedrycz, Heloisa Camargo. Fuzzy timed Petri nets[J]. Fuzzy Sets and Systems, 2003(140):301-330.
[66]Jorge C.A. de Figueiredo, Angelo Perkusich. Faults and timing analysis in real-time distributed systems:A fuzzy time Petri-net-based approach[J]. Fuzzy Sets and Systems, 1996(83):143-168.
[67]ZouHua Ding, H.Buke,M. Schneider. Fuzzy Timed Petri Net Definitions, Properties, and Applications [J]. Mathematical and Computer Modelling,2005(41):345-360.
[68]Ouali M.-S., Ait-Kadi D., Rezg. Fault diagnosis model based on Petri Net with fuzzy colors [J].Computers & Industrial Engineering,1999(37):173-176
[69]Ben-Arieh, Rajeev Ranjan Kumar, M.K. Tiwarib. Analysis of assembly operations difficulty using enhancedexpert high-level colored fuzzy Petri net model [J]. Robotics and Computer-Integrated Manufacturing,2004(20):385-403.
[70]Seung Jun Lee, Poong Hyun Seong. Development of automated operating proceduresystem using fuzzy colored petri nets for nuclearpower plants [J].Annals of Nuclear Energy,2004(31): 849-869.
[71]G.K.H. Pang, R. Tang, S.S. Woo, A process-control and diagnostic tool based on continuous fuzzy Petri nets [J]. Eng.Appl. Artif. Intell,1995(8):643-650.
[72]W Pedrycz, F. Gomide, A generalized fuzzy Petri net model [J]. IEEE Trans. Fuzzy Systems, 1994(4):295-301.
[73]鲍培明.模糊Petri网模型的反向推理算法[J].南京师范大学学报(工程技术版),2003,(3)3：21-25.
[74]鲍培明.基于查询方式的模糊Petri网的推理算法[J].计算机工程,2004(4)30,70-73.
[75]贾立新,薛钧义,茹峰.采用模糊Petri网的形式化推理算法及其应用[J].西安交通大学学报,2003,37(3)：1263-1266.
[76]林闯.Petri网用于Horn子句的逻辑推论[J].软件学报,1993,4(8)：3237.
[77]安毅生,李人厚.对象化模糊Petri网的任务协同分配建模与推理[J].计算机辅助设计与图形学学报,2006,18(5)：710714.
[78]刁永锋,陈星.基于模糊Petri网的三值产生式知识表示及推理[J].模式识别与人工智能,2005,18(3)：340344.
[79]刘剑刚,高洁,王明哲.模糊Petri网及其在模糊推理中的应用[J].计算机仿真,2004,21(11)：152154.
[80]姜浩,罗军舟,方宁生.模糊Petri网在带权不确定知识表示和推理中的应用[J].计算机研究与发展,2000,37(8)：918923.
[81]王永革.序Petri网计算能力分析[J].软件学报,1993,4(6)：3541.
[82]李凡长.动态模糊Petri网模型及其应用研究[J].小型微型计算机系统,2002,23(7)：853857.
[83]危胜军,胡昌振,孙明谦.基于模糊Petri网的动态知识表示与推理方法[J].科技导报,2007,25(7)：1317.
[84]王海峰,刘顺利,操红武.基于模糊Petri网的实时系统功能模型构建[J].现代防御技术,2005,33(3)：61-65.
[85]黄光球,朱华平,郑彦全.基于模糊Petri网的事故树模糊分析方法研究[J].湖南科技大学学报自然科学版,2006,21(2)：3439.
[86]张福平,李堂军.基于模糊Petri网的提升机制动事故分析[J].矿山机械,2007,35(9)：8689.
[87]韩光臣,孙树栋,司书宾等.基于模糊概率Petri网系统的故障诊断仿真研究[J].计算机集成制造系统,2006,12(4)：520525.
[88]杨其宇,张霞.模糊Petri网故障诊断技术应用[J].测控技术,2006,25(4)：7374.
[89]Dimitris Kiritsis & Michel Porchet. A generic Petri net model for dynamic process planning and sequence optimization [J]. Advances in Engineering Software,1996(25):61-71.
[90]Samir M. Koriem, T.E. Dabbous, W.S. El-Kilani,A new Petri net modeling technique for the performanceanalysis of discrete event dynamic sy stems [J]. The Journal of Systems and Software,2004(72):335-348.
[91]Burcin Bostan-Korpeoglu, Adnan Yazici.A fuzzy Petri net model for intelligent databases [J]. Data & Knowledge Engineering,2007(62):219-247.
[92]Sheng-Ke Yu.Knowledge representation and reasoningusing fuzzy Pr/T net-systems [J]. Fuzzy Sets and Systems,1995(75):33-45.
[93]IMRE J. RUDAS. Modeling of Manufacturing Processes Using a Petri-net Representation [J]. Engng Applic. Artif. Lntel,1997(10):243-255.
[94]Rajiv Kumar Sharma,Dinesh Kumar,Pradeep Kumar,Predicting uncertain behavior of industrial system usingFM-A practical case[J]. Applied Soft Computing,2008(8):96-109.
[95]J.Knezevic, E.R.Odoom.Reliability modeling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology[J]. Reliablity Engineering and System Safety,2001(73):1-17.
[96]Yueh-Min Huang,Juei-Nan Chen,Tien-Chi Huang,Standardized course generation process using Dynamic Fuzzy Petri Nets [J].Expert Systems with Applications,2008(34):72-86.
[97]D. J. REID. Constructing Petri Net Models Using Genetic Search Math[J]. Computer. Modelling,1998(27):85-103.
[98]C.A. Gracio Marna, E. Vargas Soto, A. Di'az Sa'nchez. Describing an IMSby a FNRTPN definition:a VHDL approach [J]. Robotics and Computer-Integrated Manufacturing,2005(21): 241-247.
[99]Witold Pedrycz.Generalized fuzzy Petri nets as pattern classifliers [J].Pattern Recognition Letters,1999(20):1489-1498.
[100]Amit Konar, Uday K. Chakraborty, Paul P. Wang. Supervised learning on a fuzzy Petri net [J]. Information Sciences,2005(172):397-416.
[101]Amit Konar,Uday K. Chakraborty,Reasoning and unsupervised learning in a fuzzy cognitive map[J].Information Sciences,2005(170):419-441.
[102]鲍培明.基于BP网络的模糊Petri网的学习能力[J].计算机学报,2004,27(5)：695-702.
[103]李洋,乐晓波.模糊Petri网与遗传算法相结合的优化策略[J].计算机应用,2006,26(1)：187-190.
[104]李洋,乐晓波.蚁群算法在模糊Petri网参数优化中的应用[J].计算机应用.2007,27(3)：638-641.
[105]Alexander Fay. A fuzzy knowledge-based system for railway traffic·control [J], Engineering Applications of Artificial Intelligence,2000 (13):719-729.
[106]潘红军,孙吉贵,元常松.层次化模糊Petri网：形式化定义和推理[J].吉林大学学报(工学版),2007,37(1)：111-116.
[107]汪洋,林闯,曲扬,李雅娟.含有否定命题逻辑推理的一致性模糊Petri网模型[J].电子学报,2006(11)：1955-1960.
[108]邢春晓,潘泉,张洪才.基于Fuzzy Petri网专家系统的研究[J].西北工业大学学报,1998(3)16：448-452.
[109]刘晓霞.基于Petri网的知识库维护方法的研究[J].小型微型计算机系统,1997,18(7)：75-78.
[110]应晶,吴朝晖,何智均.基于Petri网的知识库一致性检查系统[J].计算机研究与发 展,1992(8)：30-35.
[111]王耀南,童调生,蔡自兴.一种基于模糊Petri网的不确定知识获取方法及其应用[J].信息与控制,1993,22(8)：24-209.
[112]Wil van der Aalst & Kees van Hee. WorkFlow Management:Models, Methods and Systems[M].北京：清华大学出版社,2004.
[113]W.M.P. van der Aalst, K.M. Van Hee. Business process redesign:A Petri-net-based approach[J]. Computers in Industry,1996(29):15-26.
[114]W.M.P. van der Aalst. Re-engineering knock-out processes [J]. Decision Support Systems, 2001(30):451-468.
[115]W.M.P. van der Aalst. Formalization and verification of event-driven process chains [J]. Information and Software Technology,1999 (41):639-650.
[116]W.M.P. van der Aalst. On the automatic generation of workflow processes based on product structures [J]. Computers in Industry,1999(39):97-111.
[117]W.M.P. van der Aalst, T. Basten. Inheritance ofwork"ows:an approach to tackling problems related to change [J]. Theoretical Computer Science,2002(270):125-203.
[118]W.M.P. van der Aalst, K.M. van Hee, R.A. van der Toorn. Component-based software architectures:a framework based on inheritance of behavior [J]. Science of Computer Programming,2002 (42):129-171.
[119]W.M.P. van der Aalst, M. Stoffele, J.W.F. Wamelink. Case handling in construction [J]. Automation in Construction,2003 (12):303-320.
[120]W.M.P. van der Aalst, M.H. Jansen-Vullers, H.M.W Verbeek. Verification of the SAP reference models using EPC reduction, state-space analysis, and invariants [J]. Computers in Industry,2007 (58):578-601.
[121]W.M.P. van der Aalst, B.F. van Dongen, J. Herbst. Workflow mining:A survey of issues and approaches [J]. Data & Knowledge Engineering,2003 (47):237-267.
[122]W.M.P. van der Aalst, A.J.M.M. Weijters. Process mining:a research agenda[J]. Computers in Industry,2004 (53):231-244.
[123]W.M.P. van der Aalst. Process Mining and Security:Detecting Anomalous Process Executions and Checking Process Conformance[J]. Electronic Notes in Theoretical Computer Science,2005 (121):3-21.
[124]W.M.P. van der Aalst, A.H.M. ter Hofstede. YAWL:yet another workflow language[J]. Information Systems,2005 (30):245-275.
[125]W.M.P. van der Aalst, H.A. Reijers, A.J.M.M. Weijters. Business process mining:An industrial application [J]. Information Systems,2007 (32):713-732.
[126]A. Rozinat. W.M.P. van der Aalst. Conformance checking of processes based on monitoring real behavior[J]. Information Systems,2008(33):64-95.
[127]M. Rosemann, W.M.P. van der Aalst. A configurable reference modelling language[J]. Information Systems,2007 (32):1-23.
[128]A.K. Alves de Medeiros, W.M.P. van der Aalst, A.J.M.M. Weijters. Quantifying process equivalence based on observed behavior[J]. Data & Knowledge Engineering,2008 (64): 55-74.
[129]范玉顺.工作流管理技术基础[M].北京：清华大学出版社.2001.
[130]Laura A. Seffino, Claudia Bauzer Medeiros, Jansle V. Rocha. WOODSS—a spatial decision support system based on workflows [J]. Decision Support Systems,1999(27): 105-123.
[131]张志敏,张天桥,益建芳.科学工作流及其在空间决策支持系统中的应用[J].东北测绘,2002,25(1)：2832.
[132]贾文珏,李斌,龚健雅.基于工作流技术的动态GIS服务链研究[J].武汉大学学报·信息科学版,2005,30(11)：982985.
[133]李满春,高月明.基于工作流和GIS的土地利用规划管理信息系统体系结构研究[J].现代测绘,2004,27(5)：36.
[134]王焱,李景文,黄俊华.基于工作流和GIS的集成信息管理系统框架设计[J].地理空间信息,2006,4(6).2729.
[135]黄照强,冯学智.房产地理信息系统时空数据组织研究[J].遥感信息,2005(5)：5256
[136]江志斌.Petri网及其在制造系统建模与控制中的应用[M].北京：机械工业出版社,2004
[137]王新洲,史文中,王树良.模糊空间信息处理[M].武汉：武汉大学出版社,2003.
[138]汪培庄,李洪兴.模糊系统理论与模糊计算机[M].北京：科学出版社,1996.
[139](比)Etienne E. Kerre,黄崇福,(比)阮达.模糊集理论与近似推理[M].武汉：武汉大学出版社,2004.
[140]杨叔子.基于知识的诊断推理[M].北京：清华大学出版社,1993.
[141]杨炳儒.知识工程与知识发现[M].北京：冶金工业出版社,2000.
[142]胡运发.数据与知识工程导论[M].北京：清华大学出版社,2003.
[143]史忠植.知识工程[M].北京：清华大学出版社,1988.
[144]章兢,张小刚.数据挖掘算法及其工程应用[M].北京机械工业出版社,2006.
[145]杜世宏,王桥,泰其明.空间关系模糊描述与组合推理[M].北京：科学出版社,2007.
[146](美)Dorian Pyle著,杨冬青,马秀莉等译,唐世渭.业务建模与数据挖掘[M].北京：机械工业出版社,2005.
[147]王劲峰.空间分析[M].北京：科学出版社,2006.
[148]朱长青,史文中.空间分析建模与原理[M].北京：科学出版社,2006.
[149]林闯.随机Petri网和系统性能评价[M].北京：清华大学出版社,2000.
[150]蒋昌俊.Petri网的行为理论及其应用[M].北京：高等教育出版社,2003.
[151](美)彼得森(Petexon, J. L)著；吴哲辉译.PETRI网理论与系统模拟[M].徐州：中国矿业大学出版社,1989.
[152]WFMC. The WorkFlow Reference Model[S].TC00-1003,1995.
[153]David Hand Heikki Mannila Padhraic Smyth. Principles of Data Mining [M].北京：机械工业出版,2003.
[154]Indranil Bose,Radha K.Mahapatra. Business data mining-- a machine learning perspective [J]. Engineering Applications of Artificial Intelligence,1998 (11):675-681.
[155]Shlomit S. Pinter, Mati Golani. Discovering workflow models from activities lifespans [J].Computers in Industry,2004 (53):283～296.
[156]Andras Javor.Petri nets and AI in modeling and simulation [J]. Mathematics and Computers in Simulation,1995 (39):477～484.
[157]AMES L, PETERSON.Petri Nets [J]. Computing Surveys,1997(19):221-225.
[2]于不凡,白帆,刘明.煤矿瓦斯防治技术[M].北京：中国经济出版社.1987.
[3]中华人民共和国煤炭工业部.防治煤与瓦斯突出细则[M].北京：煤炭工业出版社,1995.
[4]程伟.煤与瓦斯突出危险性预测及防治技术[M].徐州：中国矿业大学,2003.
[5]聂百胜,何学秋,王恩元等.煤与瓦斯突出预测技术研究现状及发展趋势[J].中国安全科学学报,2003,13(6)：4043.
[6]漆旺生,凌标灿,蔡嗣经.煤与瓦斯突出预测研究动态及展望[J].中国安全科学学报,2003,13(12)：14.
[7]Wang Kai, et al. A Prediction Model for the Risk of Coal and Gas Outburst Based on Artificial Neural Network[C]. Coal Mine Safety and Health:Proceedings of the International Mining Technology'98 Symposium. Beijing:China Coal Industry Publishing House,1998:51-56
[8]俞善炳,谈庆明,丁雁生等.含气多孔介质卸压层裂的间隔特征—突出的前兆[J].力学学报,1998,30(2)：145150.
[9]苏文叔.利用瓦斯涌出动态指标预测煤与瓦斯突出[C].防治煤与瓦斯突出论文集.北京：中国煤炭工业劳动保护科学技术学会,2001.
[10]S.M. Chen, J.S. Ke, J.F. Chang, Knowledge representation using fuzzy Petri nets[J].IEEE Trans. Knowledge Data Engrg,1990,2 (3):311-319.
[11]袁崇义.Petri网原理与应用[M].北京：电子工业出版社,2005.
[12]何新贵.模糊知识处理的理论与技术[M].北京：国防工业出版社,1999.
[13]吴哲辉.Petri网导论[M].北京：机械工业出版社,2006.
[14]何新贵.模糊Petri网[J].计算机学报,1994,17(12)：946950.
[15]X. Li, F. Lara-Rosano.Adaptive fuzzy petri nets for dynamic knowledge representation and inference[J].Expert Systems with Applications,2000 (19):235-241.
[16]高艳忠,蒋承林.模糊(Fuzzy)数学在煤与瓦斯突出预测中的应用[J].江西煤炭科技,2006,2(2)：68.
[17]吴海清.模糊数学在预测煤与瓦斯突出中的应用[J].陕西煤炭技术,1992(4)：1618.
[18]陈凤,申东日等.模糊小波网络在煤与瓦斯突出预测中的应用[J].煤矿安全,2006(10)：5154.
[19]金芳勇,石必明.模糊综合评判在煤与瓦斯突出监测中的应用[J].江西煤炭科技,2006,1(1)：1012.
[20]章壮新,吴桂义.煤与瓦斯突出模糊专家系统[J].贵州工业大学学报,2001,30(3)：21-24.
[21]桂祥友,郁钟铭.基于模糊聚类关联分析法的煤与瓦斯突出程度分析[J].安全与环境学报,2006,6(4)：85-88.
[22]吴财芳,曾勇,张子戌等.基于模糊神经网络的煤与瓦斯突出区域预测研究[J].煤田地质与勘探,2002,30(6)：4-8.
[23]秦书玉.煤与瓦斯突出预报的模糊聚类相似分析法[J].中国地质灾害与防治学报,2003,14(4)：58-61.
[24]张子戌,刘高峰,吕闰生.基于模糊模式识别的煤与瓦斯突出区域预测[J].煤炭学报,2007,32(6)：592-595.
[25]李德仁,王树良,史文中等.论空间数据挖掘和知识发现[J].武汉大学学报信息科学版,2001,26(6)：491-499.
[26]孙庆先,方涛,郭达志.空间数据挖掘技术中的区划效应及在矿山中的应用[J].煤炭学报,2007,(32)8：804-807.
[27]张光建,王立杰,汪文生.用空间数据挖掘技术提升煤矿安全管理水平[J].煤矿安全,2005(7)：51-53.
[28]王凯,王轶波,卢杰.煤与瓦斯突出动态前兆的非线性特征研究[J].采矿与安全工程学报,2007,24(1)：22-24.
[29]李成武.区域煤与瓦斯突出危险性动态评价方法[J].煤矿安全,2007(5)：64-66.
[30]毛善君,郑升飞.煤和瓦斯的动态预测[J].煤田地质与勘探,1992,20(2)：36-39.
[31]章立清,秦玉金,姜文忠等.我国矿井瓦斯涌出量预测方法研究现状及展望[J].煤矿安全,2007,393(8)：58-60.
[32]张耀平,叶青,贾真真,江文武.工作面瓦斯涌出量预测及瓦斯来源分析[J].中国矿业,2007,11(16)：46-52.
[33]魏建平,龙威成,刘明举,王根卿.鹤壁八矿瓦斯赋存规律及其主要控制因素分析[J].煤矿安全,2007(5)：61-63.
[34]王以功,林晓霞,杨晓东,戴仁竹.基于工作流的煤矿安全信息管理系统建模[J].中国矿业,2007,11(16)：43-45.
[35]邱进伟,张国枢.基于模糊优选的矿井通风系统决策研究[J].煤矿安全,2007(4)：1-4.
[36]李飒.基于数据仓库的煤矿安全信息管理系统设计[J].煤矿安全,2007(2)：60-62.
[37]刘泽宇.矿井瓦斯安全智能巡检系统在古书院矿的应用[J].煤矿安全,2007(5)：58-60.
[38]王恩营.利用瓦斯涌出量计算瓦斯含量的方法及可靠性评价[J].煤矿开采,2007(12)：1-2.
[39]殷秋朝,张小东.利用瓦斯涌出量计算瓦斯含量的方法在大平矿的实践[J].煤矿安全,2007,(9)：19-22.
[40]易伟欣.爆层瓦斯含量晌地质要素分析及预测[J].中州煤炭,2007(1)：71-73.
[41]李成武.煤与瓦斯突出危险性灰色分类方法实验研究[J].煤矿安全,2007(6)：1-4.
[42]赵旭生.“低指标突出现象”原因分析及防范对策[J].煤矿安全,2007(5)：67-69.
[43]别玉平,高军伟,魏风清.长虹公司二煤层煤与瓦斯突出危险性区域预测[J].中州煤炭,2007(4)：80-82.
[44]张连成,张建民.超前钻释放瓦斯防治严重突出危险煤层煤与瓦斯突出[J].煤矿安全,2007(6)：58-60.
[45]刘明举,牟全斌,魏建平等.新安煤矿瓦斯赋存规律及影响因素探讨[J].煤矿安全,2007(11)：60-62.
[46]陈胜利.徐州矿区瓦斯涌出规律探讨[J].煤炭科技,2007(4)：77-79.
[47]王清亮.智能决策理论在矿井通风系统中的应用研究[J].煤矿安全,2007(4)：5-8.
[48]于不凡,王佑安.煤矿瓦斯灾害防治及利用技术手册[M].北京：煤炭工业出版社,2000.
[49]张子戌,袁崇孚.瓦斯地质数学模型方法[J].煤炭学报,1999,24(4)：8-12.
[50]秦汝祥.煤与瓦斯突出预报研究现状综述[J].能源技术与管理,2005(1)：7-9.
[51]A.J. Bugarin, S. Barro. Fuzzy reasoning supported by Petri nets[J]. IEEE Trans. Fuzzy Systems,1994(2):135-150.
[52]T. Cao, A.C. Sanderson, Task sequence planning using fuzzy Petri nets [J]. IEEE Trans. Systems Man Cybernet,1995,25 (5):755-769.
[53]J. Cardoso, R. Valette, D. Dubois. Petri nets with uncertain markings, in:G. Rozenberg (Ed.),Advances in Petri Nets, Lecture Notes in Computer Science, Springer-Verlag, New York, 1990:65-78.
[54]Andreu, D., Pascal, J.,& Valette, R. Fuzzy Petri net-based programmable logic controller [J]. IEEE Transactions on SMC—Part B:Cybernetics,1997(27):952-961.
[55]Hanna, M. M., Buck, A.,& Smith, R. Fuzzy Petri nets with neural networks to model products quality from a CNC-milling machining centre [J]. IEEE Transactions on SMC, Part A: Systems and Humans,1996(26):638-645.
[56]M.L. Garg, S.I. Ashon, P.V. Gupta. A fuzzy Petri net for knowledge representation and reasoning[J]. Inform. Process. Lett,1991(39):165-171.
[57]T. Cao, A.C. Sanderson. A fuzzy Petri net approach to reasoning about uncertainty in Robotic systems, in:Proc. IEEE Int. Conf. Robotics and Automation,1993:317-322.
[58]Scarpelli, H.,& Gomide, F. A high-level fuzzy net approach for discovering potential inconsistencies in fuzzy knowledge bases [J]. Fuzzy Sets and Systems,1994(64):175-193.
[59]A. Konar, A.K. Mandal, Uncertainty management in expert systems using fuzzy Petri nets,IEEE Ttrans[J]. Knowledge Data Engrg,1996,8(1):96-105.
[60]Scarpelli, H.,& Gomide, F. Fuzzy reasoning and fuzzy Petri nets in manufacturing systems modeling[J]. Journal of Intelligent Fuzzy Systems,1993(1):225-241.
[61]C.G. Looney, Fuzzy Petri nets for rule-based decision making [J]. IEEE Trans. Systems Man Cybernet,1988,18 (1):178-183.
[62]Tang, R., Pang, G. K. H.,& Woo, S. S. A continuous fuzzy Petri net tool for intelligent process monitoring and control [J]. IEEE Transactions on Control System Technology, 1995(3):318-329.
[63]Yeung, D. S.,& Tsang, E. C. C. Fuzzy knowledge representation and reasoning using Petri nets[J]. Expert System Application,1994 (7):281-290
[64]W. Pedrycz. A fuzzy cognitive structure for pattern recognition [J]. Pattern Recognition Lett, 1989(9):305-313.
[65]Witold Pedrycz, Heloisa Camargo. Fuzzy timed Petri nets[J]. Fuzzy Sets and Systems, 2003(140):301-330.
[66]Jorge C.A. de Figueiredo, Angelo Perkusich. Faults and timing analysis in real-time distributed systems:A fuzzy time Petri-net-based approach[J]. Fuzzy Sets and Systems, 1996(83):143-168.
[67]ZouHua Ding, H.Buke,M. Schneider. Fuzzy Timed Petri Net Definitions, Properties, and Applications [J]. Mathematical and Computer Modelling,2005(41):345-360.
[68]Ouali M.-S., Ait-Kadi D., Rezg. Fault diagnosis model based on Petri Net with fuzzy colors [J].Computers & Industrial Engineering,1999(37):173-176
[69]Ben-Arieh, Rajeev Ranjan Kumar, M.K. Tiwarib. Analysis of assembly operations difficulty using enhancedexpert high-level colored fuzzy Petri net model [J]. Robotics and Computer-Integrated Manufacturing,2004(20):385-403.
[70]Seung Jun Lee, Poong Hyun Seong. Development of automated operating proceduresystem using fuzzy colored petri nets for nuclearpower plants [J].Annals of Nuclear Energy,2004(31): 849-869.
[71]G.K.H. Pang, R. Tang, S.S. Woo, A process-control and diagnostic tool based on continuous fuzzy Petri nets [J]. Eng.Appl. Artif. Intell,1995(8):643-650.
[72]W Pedrycz, F. Gomide, A generalized fuzzy Petri net model [J]. IEEE Trans. Fuzzy Systems, 1994(4):295-301.
[73]鲍培明.模糊Petri网模型的反向推理算法[J].南京师范大学学报(工程技术版),2003,(3)3：21-25.
[74]鲍培明.基于查询方式的模糊Petri网的推理算法[J].计算机工程,2004(4)30,70-73.
[75]贾立新,薛钧义,茹峰.采用模糊Petri网的形式化推理算法及其应用[J].西安交通大学学报,2003,37(3)：1263-1266.
[76]林闯.Petri网用于Horn子句的逻辑推论[J].软件学报,1993,4(8)：3237.
[77]安毅生,李人厚.对象化模糊Petri网的任务协同分配建模与推理[J].计算机辅助设计与图形学学报,2006,18(5)：710714.
[78]刁永锋,陈星.基于模糊Petri网的三值产生式知识表示及推理[J].模式识别与人工智能,2005,18(3)：340344.
[79]刘剑刚,高洁,王明哲.模糊Petri网及其在模糊推理中的应用[J].计算机仿真,2004,21(11)：152154.
[80]姜浩,罗军舟,方宁生.模糊Petri网在带权不确定知识表示和推理中的应用[J].计算机研究与发展,2000,37(8)：918923.
[81]王永革.序Petri网计算能力分析[J].软件学报,1993,4(6)：3541.
[82]李凡长.动态模糊Petri网模型及其应用研究[J].小型微型计算机系统,2002,23(7)：853857.
[83]危胜军,胡昌振,孙明谦.基于模糊Petri网的动态知识表示与推理方法[J].科技导报,2007,25(7)：1317.
[84]王海峰,刘顺利,操红武.基于模糊Petri网的实时系统功能模型构建[J].现代防御技术,2005,33(3)：61-65.
[85]黄光球,朱华平,郑彦全.基于模糊Petri网的事故树模糊分析方法研究[J].湖南科技大学学报自然科学版,2006,21(2)：3439.
[86]张福平,李堂军.基于模糊Petri网的提升机制动事故分析[J].矿山机械,2007,35(9)：8689.
[87]韩光臣,孙树栋,司书宾等.基于模糊概率Petri网系统的故障诊断仿真研究[J].计算机集成制造系统,2006,12(4)：520525.
[88]杨其宇,张霞.模糊Petri网故障诊断技术应用[J].测控技术,2006,25(4)：7374.
[89]Dimitris Kiritsis & Michel Porchet. A generic Petri net model for dynamic process planning and sequence optimization [J]. Advances in Engineering Software,1996(25):61-71.
[90]Samir M. Koriem, T.E. Dabbous, W.S. El-Kilani,A new Petri net modeling technique for the performanceanalysis of discrete event dynamic sy stems [J]. The Journal of Systems and Software,2004(72):335-348.
[91]Burcin Bostan-Korpeoglu, Adnan Yazici.A fuzzy Petri net model for intelligent databases [J]. Data & Knowledge Engineering,2007(62):219-247.
[92]Sheng-Ke Yu.Knowledge representation and reasoningusing fuzzy Pr/T net-systems [J]. Fuzzy Sets and Systems,1995(75):33-45.
[93]IMRE J. RUDAS. Modeling of Manufacturing Processes Using a Petri-net Representation [J]. Engng Applic. Artif. Lntel,1997(10):243-255.
[94]Rajiv Kumar Sharma,Dinesh Kumar,Pradeep Kumar,Predicting uncertain behavior of industrial system usingFM-A practical case[J]. Applied Soft Computing,2008(8):96-109.
[95]J.Knezevic, E.R.Odoom.Reliability modeling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology[J]. Reliablity Engineering and System Safety,2001(73):1-17.
[96]Yueh-Min Huang,Juei-Nan Chen,Tien-Chi Huang,Standardized course generation process using Dynamic Fuzzy Petri Nets [J].Expert Systems with Applications,2008(34):72-86.
[97]D. J. REID. Constructing Petri Net Models Using Genetic Search Math[J]. Computer. Modelling,1998(27):85-103.
[98]C.A. Gracio Marna, E. Vargas Soto, A. Di'az Sa'nchez. Describing an IMSby a FNRTPN definition:a VHDL approach [J]. Robotics and Computer-Integrated Manufacturing,2005(21): 241-247.
[99]Witold Pedrycz.Generalized fuzzy Petri nets as pattern classifliers [J].Pattern Recognition Letters,1999(20):1489-1498.
[100]Amit Konar, Uday K. Chakraborty, Paul P. Wang. Supervised learning on a fuzzy Petri net [J]. Information Sciences,2005(172):397-416.
[101]Amit Konar,Uday K. Chakraborty,Reasoning and unsupervised learning in a fuzzy cognitive map[J].Information Sciences,2005(170):419-441.
[102]鲍培明.基于BP网络的模糊Petri网的学习能力[J].计算机学报,2004,27(5)：695-702.
[103]李洋,乐晓波.模糊Petri网与遗传算法相结合的优化策略[J].计算机应用,2006,26(1)：187-190.
[104]李洋,乐晓波.蚁群算法在模糊Petri网参数优化中的应用[J].计算机应用.2007,27(3)：638-641.
[105]Alexander Fay. A fuzzy knowledge-based system for railway traffic·control [J], Engineering Applications of Artificial Intelligence,2000 (13):719-729.
[106]潘红军,孙吉贵,元常松.层次化模糊Petri网：形式化定义和推理[J].吉林大学学报(工学版),2007,37(1)：111-116.
[107]汪洋,林闯,曲扬,李雅娟.含有否定命题逻辑推理的一致性模糊Petri网模型[J].电子学报,2006(11)：1955-1960.
[108]邢春晓,潘泉,张洪才.基于Fuzzy Petri网专家系统的研究[J].西北工业大学学报,1998(3)16：448-452.
[109]刘晓霞.基于Petri网的知识库维护方法的研究[J].小型微型计算机系统,1997,18(7)：75-78.
[110]应晶,吴朝晖,何智均.基于Petri网的知识库一致性检查系统[J].计算机研究与发 展,1992(8)：30-35.
[111]王耀南,童调生,蔡自兴.一种基于模糊Petri网的不确定知识获取方法及其应用[J].信息与控制,1993,22(8)：24-209.
[112]Wil van der Aalst & Kees van Hee. WorkFlow Management:Models, Methods and Systems[M].北京：清华大学出版社,2004.
[113]W.M.P. van der Aalst, K.M. Van Hee. Business process redesign:A Petri-net-based approach[J]. Computers in Industry,1996(29):15-26.
[114]W.M.P. van der Aalst. Re-engineering knock-out processes [J]. Decision Support Systems, 2001(30):451-468.
[115]W.M.P. van der Aalst. Formalization and verification of event-driven process chains [J]. Information and Software Technology,1999 (41):639-650.
[116]W.M.P. van der Aalst. On the automatic generation of workflow processes based on product structures [J]. Computers in Industry,1999(39):97-111.
[117]W.M.P. van der Aalst, T. Basten. Inheritance ofwork"ows:an approach to tackling problems related to change [J]. Theoretical Computer Science,2002(270):125-203.
[118]W.M.P. van der Aalst, K.M. van Hee, R.A. van der Toorn. Component-based software architectures:a framework based on inheritance of behavior [J]. Science of Computer Programming,2002 (42):129-171.
[119]W.M.P. van der Aalst, M. Stoffele, J.W.F. Wamelink. Case handling in construction [J]. Automation in Construction,2003 (12):303-320.
[120]W.M.P. van der Aalst, M.H. Jansen-Vullers, H.M.W Verbeek. Verification of the SAP reference models using EPC reduction, state-space analysis, and invariants [J]. Computers in Industry,2007 (58):578-601.
[121]W.M.P. van der Aalst, B.F. van Dongen, J. Herbst. Workflow mining:A survey of issues and approaches [J]. Data & Knowledge Engineering,2003 (47):237-267.
[122]W.M.P. van der Aalst, A.J.M.M. Weijters. Process mining:a research agenda[J]. Computers in Industry,2004 (53):231-244.
[123]W.M.P. van der Aalst. Process Mining and Security:Detecting Anomalous Process Executions and Checking Process Conformance[J]. Electronic Notes in Theoretical Computer Science,2005 (121):3-21.
[124]W.M.P. van der Aalst, A.H.M. ter Hofstede. YAWL:yet another workflow language[J]. Information Systems,2005 (30):245-275.
[125]W.M.P. van der Aalst, H.A. Reijers, A.J.M.M. Weijters. Business process mining:An industrial application [J]. Information Systems,2007 (32):713-732.
[126]A. Rozinat. W.M.P. van der Aalst. Conformance checking of processes based on monitoring real behavior[J]. Information Systems,2008(33):64-95.
[127]M. Rosemann, W.M.P. van der Aalst. A configurable reference modelling language[J]. Information Systems,2007 (32):1-23.
[128]A.K. Alves de Medeiros, W.M.P. van der Aalst, A.J.M.M. Weijters. Quantifying process equivalence based on observed behavior[J]. Data & Knowledge Engineering,2008 (64): 55-74.
[129]范玉顺.工作流管理技术基础[M].北京：清华大学出版社.2001.
[130]Laura A. Seffino, Claudia Bauzer Medeiros, Jansle V. Rocha. WOODSS—a spatial decision support system based on workflows [J]. Decision Support Systems,1999(27): 105-123.
[131]张志敏,张天桥,益建芳.科学工作流及其在空间决策支持系统中的应用[J].东北测绘,2002,25(1)：2832.
[132]贾文珏,李斌,龚健雅.基于工作流技术的动态GIS服务链研究[J].武汉大学学报·信息科学版,2005,30(11)：982985.
[133]李满春,高月明.基于工作流和GIS的土地利用规划管理信息系统体系结构研究[J].现代测绘,2004,27(5)：36.
[134]王焱,李景文,黄俊华.基于工作流和GIS的集成信息管理系统框架设计[J].地理空间信息,2006,4(6).2729.
[135]黄照强,冯学智.房产地理信息系统时空数据组织研究[J].遥感信息,2005(5)：5256
[136]江志斌.Petri网及其在制造系统建模与控制中的应用[M].北京：机械工业出版社,2004
[137]王新洲,史文中,王树良.模糊空间信息处理[M].武汉：武汉大学出版社,2003.
[138]汪培庄,李洪兴.模糊系统理论与模糊计算机[M].北京：科学出版社,1996.
[139](比)Etienne E. Kerre,黄崇福,(比)阮达.模糊集理论与近似推理[M].武汉：武汉大学出版社,2004.
[140]杨叔子.基于知识的诊断推理[M].北京：清华大学出版社,1993.
[141]杨炳儒.知识工程与知识发现[M].北京：冶金工业出版社,2000.
[142]胡运发.数据与知识工程导论[M].北京：清华大学出版社,2003.
[143]史忠植.知识工程[M].北京：清华大学出版社,1988.
[144]章兢,张小刚.数据挖掘算法及其工程应用[M].北京机械工业出版社,2006.
[145]杜世宏,王桥,泰其明.空间关系模糊描述与组合推理[M].北京：科学出版社,2007.
[146](美)Dorian Pyle著,杨冬青,马秀莉等译,唐世渭.业务建模与数据挖掘[M].北京：机械工业出版社,2005.
[147]王劲峰.空间分析[M].北京：科学出版社,2006.
[148]朱长青,史文中.空间分析建模与原理[M].北京：科学出版社,2006.
[149]林闯.随机Petri网和系统性能评价[M].北京：清华大学出版社,2000.
[150]蒋昌俊.Petri网的行为理论及其应用[M].北京：高等教育出版社,2003.
[151](美)彼得森(Petexon, J. L)著；吴哲辉译.PETRI网理论与系统模拟[M].徐州：中国矿业大学出版社,1989.
[152]WFMC. The WorkFlow Reference Model[S].TC00-1003,1995.
[153]David Hand Heikki Mannila Padhraic Smyth. Principles of Data Mining [M].北京：机械工业出版,2003.
[154]Indranil Bose,Radha K.Mahapatra. Business data mining-- a machine learning perspective [J]. Engineering Applications of Artificial Intelligence,1998 (11):675-681.
[155]Shlomit S. Pinter, Mati Golani. Discovering workflow models from activities lifespans [J].Computers in Industry,2004 (53):283～296.
[156]Andras Javor.Petri nets and AI in modeling and simulation [J]. Mathematics and Computers in Simulation,1995 (39):477～484.
[157]AMES L, PETERSON.Petri Nets [J]. Computing Surveys,1997(19):221-225.