基于WSN的船舶危险品运输风险预警模型与仿真研究
|
摘要
船舶运输是世界上最主要的运输方式之一,其中有超过半数以上的船载货物属于危险品。危险品在运输过程中安全控制的复杂度高,管理难度大,事故时有发生。一旦事故发生,就会对生命、财产和环境造成重大威胁。船舶危险品运输的安全问题一直是世人所关注的热点问题。尽管目前有关部门对危险品运输的安全管理做了大量工作,但是仍旧难以彻底解决危险品运输的安全问题。对船舶运输过程中货物的安全状态进行有效监控,实现风险预警,保障运输安全,是当前亟待解决的一个现实问题。本文针对船载包装危险品,围绕其运输途中的状态监测和风险预警问题开展了以下几方面的研究工作：
(1)将无线传感器网络用于对舱室内表征货物安全状态的环境信息的监控,从而达到掌握危险货物安全状态的目的,设计了适用于船上实施的无线传感器网络拓扑结构,并通过实船实验验证了其可行性。
(2)将时间序列分析方法引入危险品安全状态的预测问题中,在基于单传感器的货物安全状态信息的分析、预测中,针对传统的差分方法在时间序列平稳化过程中容易造成有价值信息丢失,影响计算精度的问题,提出了一种指数平滑法和自回归移动法的组合方法；在基于多传感器的信息融合研究中,提出了基于协整理论的船载危险品在途安全状态信息融合处理方法,该方法发挥多传感器的优势,可对危险品在途状态信息进行较为准确的预测,同时具有异常状态的诊断功能。
(3)为掌握船载危险品处于异常状态下的危险态势演变过程,提出将计算流体力学数值模拟方法引入到船舶包装危险品运输风险监测预警问题的研究中,采用该方法在船舱内有危险气体产生的情况下,对危险气体的泄漏、扩散进行了数值计算和动态仿真。同时,结合相应的物理实验对方法的可行性予以验证,实验结果表明,计算流体力学数值模拟方法应用于船舶包装危险品运输风险预警问题可行、有效。
(4)为指导船上人员对货物异常状态进行应急处置,提出一种将无线传感器网络监测和计算流体力学数值模拟有机结合的新方法,实现对船载包装危险品异常状态的态势判定。该方法一方面将无线传感器网络作为危险货物状态的监测手段,另一方面采用计算流体力学方法事先对运输过程中可能出现的典型异常状态做数值模拟,最后运用模式识别方法将二者有机结合,实现对船载危险品异常状态的态势判定。在该模式识别的相似性度量问题研究中,针对大数据量情况下现有的动态时间弯曲算法复杂度高、计算效率低的问题,提出了一种基于动态时间弯曲的模式距离滑动窗口算法。
Sea shipping is one of the most leading transportation ways for world trade, and more than half ship cargos belong to dangerous goods. As is well known, the security control and management to the transportation for dangerous cargos is very difficult to execute extremely well, which leads to the accidents happen frequently. Once an accident happens, it will cause serious threat to human life, natural environment and economy. As a result, the safety of water transportation for dangerous cargos has drawn common people's attention. For present, a lot of safety management work has been done to dangerous goods transportation, but it does not go far enough to ensure transportation safety. So, it is an urgent issue to monitor the safety state of dangerous shipping cargo when they are in transit, which can realize the risk early warning and ensure the safety of dangerous cargo transportation. Aimed at this problem and focused on the package dangerous cargos and their state monitoring and risk early warning, this article will take researches form the following aspects:
(1) In order to know well the security status of dangerous goods on board, wireless sensor network is used to monitor the environment information which indicates the safety of dangerous goods, and the wireless sensor network topology control method fit to ship is designed and tested by this paper.
(2) Time series analysis is leaded into early warning for the safety of dangerous goods. In the analysis and early warning of dangerous goods security status information from single sensor, traditional difference method would lose the valuable information and influence the precision of early warning in the process of flatting time series. According to this situation, the exponential smoothing and autoregressive moving average are proposed. In the multi-sensor information fusion research, the paper proposes an algorithm for ship-borne dangerous goods in-transit security status information fusion based on co-integration theory, the algorithm plays the advantages of multi-sensor, can predict the dangerous goods status information accurately, and simultaneously, and diagnose whether the status is normal or not.
(3) To master the evolution of the risk situation of the ship dangerous goods in abnormal state, Proposes that lead CFD numerical simulation method into the researches of ship packaged dangerous goods transport risk monitoring and early warning, in the case of hazardous gases in cargo hold, leakage and diffusion of hazardous gases are calculated and dynamic simulation by using this method. Meanwhile, combines the corresponding physical experiment to test the feasibility of the method, experimental results show that CFD numerical simulation method used in risk early warning of ship packaged dangerous goods transport is feasible and effective.
(4) In order to provide guidance for ship's officer to emergency disposal of shipping cargos'abnormal condition, a new way to judge the abnormal condition of shipping dangerous package goods is realized on the basis of combining technologies of the WSN monitoring and CFD numerical modeling. In this way, the WSN is used as the tool for monitoring dangerous goods state, and the CFD is used to do numerical model for the typical abnormal state in transit, then these two technologies are combined by the use of Pattern Recognition to judge the state of the shipping dangerous cargos. In the research of similarity measuring method of Pattern Recognition, aimed at the high complexity and low computational efficiency of the existing Dynamic Time Warp (DTW) algorithm, a pattern distance sliding window algorithm based on DTW is presented in this article.
(1)将无线传感器网络用于对舱室内表征货物安全状态的环境信息的监控,从而达到掌握危险货物安全状态的目的,设计了适用于船上实施的无线传感器网络拓扑结构,并通过实船实验验证了其可行性。
(2)将时间序列分析方法引入危险品安全状态的预测问题中,在基于单传感器的货物安全状态信息的分析、预测中,针对传统的差分方法在时间序列平稳化过程中容易造成有价值信息丢失,影响计算精度的问题,提出了一种指数平滑法和自回归移动法的组合方法；在基于多传感器的信息融合研究中,提出了基于协整理论的船载危险品在途安全状态信息融合处理方法,该方法发挥多传感器的优势,可对危险品在途状态信息进行较为准确的预测,同时具有异常状态的诊断功能。
(3)为掌握船载危险品处于异常状态下的危险态势演变过程,提出将计算流体力学数值模拟方法引入到船舶包装危险品运输风险监测预警问题的研究中,采用该方法在船舱内有危险气体产生的情况下,对危险气体的泄漏、扩散进行了数值计算和动态仿真。同时,结合相应的物理实验对方法的可行性予以验证,实验结果表明,计算流体力学数值模拟方法应用于船舶包装危险品运输风险预警问题可行、有效。
(4)为指导船上人员对货物异常状态进行应急处置,提出一种将无线传感器网络监测和计算流体力学数值模拟有机结合的新方法,实现对船载包装危险品异常状态的态势判定。该方法一方面将无线传感器网络作为危险货物状态的监测手段,另一方面采用计算流体力学方法事先对运输过程中可能出现的典型异常状态做数值模拟,最后运用模式识别方法将二者有机结合,实现对船载危险品异常状态的态势判定。在该模式识别的相似性度量问题研究中,针对大数据量情况下现有的动态时间弯曲算法复杂度高、计算效率低的问题,提出了一种基于动态时间弯曲的模式距离滑动窗口算法。
Sea shipping is one of the most leading transportation ways for world trade, and more than half ship cargos belong to dangerous goods. As is well known, the security control and management to the transportation for dangerous cargos is very difficult to execute extremely well, which leads to the accidents happen frequently. Once an accident happens, it will cause serious threat to human life, natural environment and economy. As a result, the safety of water transportation for dangerous cargos has drawn common people's attention. For present, a lot of safety management work has been done to dangerous goods transportation, but it does not go far enough to ensure transportation safety. So, it is an urgent issue to monitor the safety state of dangerous shipping cargo when they are in transit, which can realize the risk early warning and ensure the safety of dangerous cargo transportation. Aimed at this problem and focused on the package dangerous cargos and their state monitoring and risk early warning, this article will take researches form the following aspects:
(1) In order to know well the security status of dangerous goods on board, wireless sensor network is used to monitor the environment information which indicates the safety of dangerous goods, and the wireless sensor network topology control method fit to ship is designed and tested by this paper.
(2) Time series analysis is leaded into early warning for the safety of dangerous goods. In the analysis and early warning of dangerous goods security status information from single sensor, traditional difference method would lose the valuable information and influence the precision of early warning in the process of flatting time series. According to this situation, the exponential smoothing and autoregressive moving average are proposed. In the multi-sensor information fusion research, the paper proposes an algorithm for ship-borne dangerous goods in-transit security status information fusion based on co-integration theory, the algorithm plays the advantages of multi-sensor, can predict the dangerous goods status information accurately, and simultaneously, and diagnose whether the status is normal or not.
(3) To master the evolution of the risk situation of the ship dangerous goods in abnormal state, Proposes that lead CFD numerical simulation method into the researches of ship packaged dangerous goods transport risk monitoring and early warning, in the case of hazardous gases in cargo hold, leakage and diffusion of hazardous gases are calculated and dynamic simulation by using this method. Meanwhile, combines the corresponding physical experiment to test the feasibility of the method, experimental results show that CFD numerical simulation method used in risk early warning of ship packaged dangerous goods transport is feasible and effective.
(4) In order to provide guidance for ship's officer to emergency disposal of shipping cargos'abnormal condition, a new way to judge the abnormal condition of shipping dangerous package goods is realized on the basis of combining technologies of the WSN monitoring and CFD numerical modeling. In this way, the WSN is used as the tool for monitoring dangerous goods state, and the CFD is used to do numerical model for the typical abnormal state in transit, then these two technologies are combined by the use of Pattern Recognition to judge the state of the shipping dangerous cargos. In the research of similarity measuring method of Pattern Recognition, aimed at the high complexity and low computational efficiency of the existing Dynamic Time Warp (DTW) algorithm, a pattern distance sliding window algorithm based on DTW is presented in this article.
引文
[1]国际海事组织.国际海运危险货物规则(2004年版)[M].大连危险货物运输研究中心译,中华人民共和国海事局,2006.
[2]http://www.shmsa.gov.cn/NewsContent.aspx?CatalogId=4a6ef228-096d-444d-9194-af328c73f7 61 & Content Id=1376291e-8bb1-4848-8755-8f5aec381f42 [EB/OL].
[3]Lee K, Ni S. On the dynamic effects of oil price shocks:a study using industry level data[J]. Journal of Monetary Economics,2002,49(4):823-852.
[4]Atkeson A, Kehoe P J. Models of energy use:Putty-putty versus putty-clay[J]. The American Economic Review,1999,89(4):1028-1043.
[5]Webb I R, Larson R C. Period and phase of customer replenishment:A new approach to the strategic inventory/routing problem[J]. European Journal of Operational Research,1995,85(1): 132-148.
[6]刘庆华.基于现金流量的企业财务预警系统研究[D]：(博士论文).成都：西南财经大学,2006.
[7]冯征.数据挖掘方法在财务预警中的应用研究[D]：(博士论文).天津：天津大学,2007.
[8]鄢志娟.基于现金流量的企业财务危机预警系统分析[J].改革与战略,2008,24(8)：144-147.
[9]Mitchell J V. A new political economy of oil[J]. The Quarterly Review of Economics and Finance,2002,42(2):251-272.
[10]Bentley R W. Global oil & gas depletion:an overview[J]. Energy policy,2002,30(3):189-205.
[11]袁志祥,单修政,徐世芳,等.地震预警技术综述[J].自然灾害学报,2007,16(6)：216-223.
[12]唐晓纯,苟变丽.食品安全预警体系框架构建研究[J].食品科学,2005,26(12)：246-250.
[13]李万莲.我国生态安全预警研究进展[J].安全与环境工程,2008,15(03)：78-81.
[14]曹明贵,马海.构建城镇贫困人口的预警机制模型[J].信阳师范学院学报：哲学社会科学版,2011,31(001)：37-41.
[15]佘丛国,席酉民.我国企业预警研究理论综述[J].预测,2003,2(003)：23-29.
[16]李明.城市房地产预警技术研究[J].数理统计与管理,2006,25(3)：315-320.
[17]黄礼,李万超.主成分分析法在财务预警实证研究中的应用[J].统计与信息论坛,2003,18(5)：83-86.
[18]陈虎虎,钟方平,许学忠,等.基于支持向量机的低空飞行目标声识别[J].系统工程与电子技术,2005,27(1)：46-48.
[19]韩郁葱,郜兵.模糊综合评判在设备故障预警专家系统中的应用[J].合肥工业大学学报(自然科学版),2007,30(6)：746-749.
[20]史成东,边敦新,苏菊宁.基于粗糙集和灰色的供应链知识共享风险预警[J].计算机工程与应用,2008,44(11)：19-22.
[21]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报,2004,25(4)：114-124.
[22]倪明选,刘云浩,朱燕民.无线传感网络的基础理论及关键技术研究[J].中国基础科学,2008,10(1)：24-28.
[23]叶嘉.设备监控无线传感器网络路由协议的设计与实现[D]：(硕士论文).长沙：国防科技大学,2006.
[24]何思远.基于无线传感器网络的瓦斯监测系统的研究[D]：(硕士论文).昆明：昆明理工大学,2007.
[25]张坚林.基于无线传感器网络的远程健康监控应用研究[D]：(硕士论文).南昌大学,2007.
[26]陈斌,万江文,冯仁剑,等.基于WSN的高速公路监控系统智能化研究[J].微纳电子技术,2007,44(7)：442-445.
[27]Mou Ruifang. Environmental risk assessment model on dangerous goods during transportation [C].2010 8th International Conference on Supply Chain Management and Information Systems (SCMIS), Hong Kong.2010:1-5.
[28]Erkut Erhan, Ingolfsson Armann. Transport risk models for hazardous materials:revisited[J]. Operations Research Letters,2005,33(1):81-89.
[29]Li Rongrong, Leung Yee. Multi-objective route planning for dangerous goods using compromise programming[J]. Journal of Geographical Systems,2011,13(3):249-271.
[30]Erhan Erkut Vedat Veter. Modeling of transport risk for hazardous materials[J]. Operations Research,1998,46(5):625-642.
[31]高清平.不确定条件下危险货物公路运输风险分析、路径选择与网络优化研究[D]：(博士论文).成都：西南交通大学,2010.
[32]黄森.危险品运输风险评价体系及路径选择研究[D]：(硕士论文).沈阳：沈阳工业大学2010.
[33]Xuesong Cai, Junwei Wu. Hazardous Chemicals Vehicles Rollover Pre-warning System Based on CPS[C].2012 IEEE Sixth International Conference on Software Security and Reliability Companion (SERE-C), Gaithersburg, MD,2012:184-187.
[34]王云鹏,孙文财,隗海林,等.基于侧倾的运输液态危险化学品的罐式半挂汽车危险状态辨识[J].吉林大学学报(工学版),2010,40(03)：640-644.
[35]陶存新,严新平,刘清.危险品运输预警应急联动机制研究[J].武汉理工大学学报(交通科学与工程版),2007,(06)：980-983.
[36]陶存新.危险品运输预警应急指挥系统研究[D]：(博士论文).武汉：武汉理工大学,2007.
[37]郝连胜.危险化学品罐式集装箱公路运输风险评价研究[D]：(硕士论文).上海：上海海事大学,2007.
[38]尹晋.气体类危险货物道路运输风险评价研究[D]：(硕士论文).北京：北京交通大学,2012.
[39]尚鸿雁,董千里,王旭坪,等.基于Fuzzy AHP的危险货物运输风险评估与预警[J].长安大学学报(社会科学版),2009,11(01)：21-27.
[40]郭培杰,蒋军成.模糊综合评价法在危险化学品道路运输风险评价中的应用[J].南京工业大学学报(自然科学版),2006,(05)：57-62.
[41]Cheng Jie, Wen Chao. Risk assessment model approach for dangerous goods transported by railway[J]. Journal of Transportation Security,2011,4(4):351-359.
[42]肖金梅,帅斌.铁路危险货物运输风险定量研究[J].铁道运输与经济,2010,32(10)：66-69.
[43]罗帆,刘英.机场危险品事故的预警管理体系探讨[J].武汉理工大学学报(社会科学版),2007(04)：421-424.
[44]王永刚,朱迪.航空危险品运输作业风险管理[J].中国安全生产科学技术,2012,8(07)：180-184.
[45]聂燕.航空危险品运输风险评价研究[D]：(硕士论文).成都：电子科技大学,2010.
[46]张伟.浅议危险品水路运输预警管理[J].中国水运(下半月),2010,10(07)：37-38.
[47]Donk J., de Rijke W. G. A risk-effect model for waterway transport of dangerous goods[C]. Reliability and Maintainability Symposium, Washington, DC,1995:349-355.
[48]Yu Bin, Jin Yongxing, Xiao Ying Jie, et al. Evaluation of maritime hazadous cargo transportation[C].2010 International Conference on Computer Application and System Modeling (ICCASM), Taiyuan, China,2010:438-441.
[49]王军,褚艳玲.基于模糊综合评价法的水路危险化学品运输风险评价[J].大连海事大学学报,2008,34(S1)：14-16.
[50]茅家源.危险货物水路运输预警管理研究[D]：(硕士论文).南京：南京理工大学,2008.
[51]李明珂.液化气船航运过程中的综合安全评价研究[D]：(硕士论文).大连：大连海事大学,2006.
[52]俞斌,金永兴,郑滨,等.基于证据理论的散装液体化学品船安全评估[J].中国航海,2012,35(01)：90-93.
[53]俞斌.不确定条件下散装液体化学品船安全评价方法及应用研究[D]：(博士论文).上海：上 海海事大学,2011.
[54]Lee Jae-Ho. A Traffic-Aware Energy Efficient Scheme for WSN Employing an Adaptable Wakeup Period[J]. Wireless Personal Communications,2012,7(3):1879-1914.
[55]Xu Xiaorong, Zhang Jianwu, Huang Aiping, et al. An adaptive measurement scheme based on compressed sensing for wideband spectrum detection in cognitive WSN[J]. Journal of Electronics (China),2012,29(6):585-592.
[56]Wang WenJie, Yao BoBin, Yin QinYe. AOD estimation in WSN localization system with synthetic aperture technique[J]. Science China Information Sciences,2012,55(10):2216-2225.
[57]Wu Guowei, Lin Chi, Yao Lin, et al. A cluster based WSN fault tolerant protocol[J]. Journal of Electronics (China),2010,27(1):43-50.
[58]Padilla P., Camacho J., Macia-Fernandez G., etal. Erratum to:On the Influence of the Propagation Channel in the Performance of Energy-Efficient Geographic Routing Algorithms for Wireless Sensor Networks (WSN)[J]. Wireless Personal Communications,2013,70(1):39.
[59]Aoun Bassam, Boutaba Raouf. Clustering in WSN with Latency and Energy Consumption Constraints[J]. Journal of Network and Systems Management,2006,14(3):415-439.
[60]Popov A. L., Vendik O. G., Zubova N. A. Magnetic field intensity in near field zone of loop antenna for RFID systems[J]. Technical Physics Letters,2010,36(10):882-884.
[61]Gu Qing-hua, Lu Cai-wu, Li Fa-ben, et al. Mining production information management system in an open pit based on GIS/GPS/GPRS/RFID[J]. Journal of Coal Science and Engineering (China), 2010,16(2):176-181.
[62]Escribano JavierG., Garcia Andres. Human condition monitoring in hazardous locations using pervasive RFID sensor tags and energy-efficient wireless networks[J]. Journal of Zhejiang University SCIENCE,2012,13(9):674-688.
[63]He Yejun. Study of Magnetic Field Coupling Technologies in Activating RFID-SIM Card Mobile Payments[J]. Wireless Personal Communications,2012:1-12.
[64]Boccadoro Mauro, Martinelli Francesco, Pagnottelli Stefano. Constrained and quantized Kalman filtering for an RFID robot localization problem[J]. Autonomous Robots,2010, 29(3-4):235-251.
[65]Luo Zhiyong, Jiang Jing, Wang Ping. Enhanced energy-saving anticollision algorithms with improving throughput for RFID system[J]. Journal of Electronics (China),2013,30(1):40-48.
[66]Merentitis A., Kranitis N., Paschalis A., et al. Low Energy Online Self-Test of Embedded Processors in Dependable WSN Nodes[J]. Dependable and Secure Computing,2012,9(1):86-100.
[67]Otero C. E., Shaw W. H., Kostanic I., et al. Multiresponse Optimization of Stochastic WSN Deployment Using Response Surface Methodology and Desirability Functions[J]. Systems Journal, 2010,4(l):39-48.
[68]Meng-Shiuan Pan, Lun-Wu Yeh, Yen-Ann Chen, et al. A WSN-Based Intelligent Light Control System Considering User Activities and Profiles[J]. Sensors Journal,2008,8(10):1710-1721.
[69]Rida A., Li Yang, Vyas R., et al. Conductive Inkjet-Printed Antennas on Flexible Low-Cost Paper-Based Substrates for RFID and WSN Applications[J]. Antennas and Propagation Magazine, 2009,51(3):13-23.
[70]Alippi C., Camplani R., Galperti C., et al. A Robust, Adaptive, Solar-Powered WSN Framework for Aquatic Environmental Monitoring[J], Sensors Journal,2011,11(1):45-55.
[71]方来华,刘骥,魏利军,等.危险品运输车辆监控预警系统设计与开发[J].中国安全科学学报,2008,18(05)：109-115.
[72]周受钦,段战归.危险化学品运输罐式装备智能监测系统[J].集装箱化,2007(11)：10-12.
[73]张令勇,高松,钟磊,等.基于3G的危险品车辆在途监控预警系统的设计[J].山东理工大学学报(自然科学版),2010,24(01)：70-74.
[74]周军.基于GPS/GPRS/GIS的危险品运输监控系统研究与设计[D]：(硕士论文).西安：长安大学,2007.
[75]徐蓉.基于GPS/GPRS/RFID的危险品车辆监控系统的研究[D]：(硕士论文).上海：上海海事大学,2007.
[76]程志端.基于多传感器的危险品运输监控系统研究与实现[D]：(硕士论文).武汉：武汉理工大学,2011.
[77]Valente F., Zacheo G., Losito P., et al. A telecommunications framework for real-time monitoring of dangerous goods transport[C].2009 9th International Conference on Intelligent Transport Systems Telecommunications(ITST),Lille,2009:13-18.
[78]张兵,李士宁,蒋思佳,等.基于WSNs的危险品车辆在途监测预警系统[J].计算机测量与控制,2012,20(03)：630-633.
[79]鞠迎华.基于WSN和RFID的铁路危险品在途监测技术研究与实现[D]：(硕士论文).北京：北京交通大学,2012.
[80]张志华,许开立.基于物联网技术危险品运输车辆智能监控系统的设计[C].2012(沈阳)国际安全科学与技术学术研讨会,中国辽宁沈阳,2012：68-75.
[81]王开乐,钟慧玲,张智勇.基于RFID/GPS/GPRS危险品运输管理系统的研究[J].物流技术,2009,8(04)：133-135.
[82]陈春贻,朱云,黎嘉明,等.危险品运输实时监控及应急救援服务平台构建[J].中国安全科学学报,2009,19(06)：109-115.
[83]Xu Peng. Ship cabin environment monitoring system based on wireless sensor network[C]. World Automation Congress (WAC), Puerto Vallarta, Mexico,2012:1-4.
[84]Zhang Yingjun, Xing Shengwei, Xu Peng, et al. Shipping containers of dangerous goods condition monitoring system based on wireless sensor network[C].2010 6th International Conference on Networked Computing (INC), Gyeongju,2010:1-3.
[85]周园,肖洪祥,董俊飞.基于MATLAB的太阳黑子时间序列分析与仿真[J].网络安全技术与应用,2012(03)：26-28.
[86]缪海波,殷坤龙,柴波,等.基于非平稳时间序列分析的滑坡变形预测[J].地质科技情报,2009,28(04)：107-111.
[87]邓继辉,陈柏林.基于时间序列分析的滑坡变形动态预测研究[J].长江科学院院报,2012,29(10)：78-81.
[88]柴微涛,宋述军,宋学鸿.成都市城区空气污染指数的时间序列分析[J].成都理工大学学报(自然科学版),2007,(04)：485-488.
[89]李冬,周川,袁朋飞,等.基于时间序列分析的渐变性水源水质预测研究[J].环境科学与技术,2012,35(06)：184-188.
[90]卢文喜,杨磊磊,龚磊,等.基于时间序列分析改进法的地下水位动态预报——以吉林省桦甸市为例[J].吉林大学学报(地球科学版),2012,42(S1)：367-372.
[91]朱睿,张俊中,龙洋,等.时间序列模型在建筑物沉降监测中的应用[J].测绘与空间地理信息,2012,35(02)：213-216.
[92]王晓鹏,曹广超,丁生喜.基于Box-Jenkins方法的青南高原降水量时间序列分析建模与预测[J].数理统计与管理,2008(04)：565-570.
[93]李东福,董雷,礼晓飞,等.基于多尺度小波分解和时间序列法的风电场风速预测[J].华北电力大学学报(自然科学版),2012,39(02)：43-48.
[94]丁明,张立军,吴义纯.基于时间序列分析的风电场风速预测模型[J].电力自动化设备,2005,(08)：32-34.
[95]刘辉,田红旗,李燕飞.基于小波分析法与滚动式时间序列法的风电场风速短期预测优化算法[J].中南大学学报(自然科学版),2010,41(01)：370-375.
[96]杨磊磊,卢文喜,刘派,等.时间序列分析及Monte Carlo方法在降水预报中的应用[J].环境科学与技术,2011,34(05)：108-112.
[97]潘雅婧,王仰麟,彭建,等.基于小波与R/S方法的汉江中下游流域降水量时间序列分析[J].地理研究,2012,31(05)：811-820.
[98]徐方舟,宋现锋,马灵玲,等.基于DEMETER卫星观测数据的电离层离子温度时间序列 预测模型[J].遥感信息,2012(02)：25-30.
[99]王毅,赵建军,付龙文,等.基于时间序列的GPS定位误差分析[J].现代科学仪器,2012,(02)：45-49.
[100]武文华,付和平,武晓东,等.应用时间序列分析法预测黑线仓鼠和长爪沙鼠种群数量[J].内蒙古农业大学学报(自然科学版),2007(04)：6-11.
[101]蒙玉波.时间序列分析在居民消费水平指数预测中的应用[J].广西师范学院学报(自然科学版),2012,29(01)：37-44.
[102]甘小冰,陶大俊.基于小波时间序列分析的电子银行风险预测[J].现代电子技术,2012,35(15)：70-71.
[103]殷文军,彭晓武,宋世震,等.广州市空气污染与城区居民心脑血管疾病死亡的时间序列分析[J].环境与健康杂志,2012,29(06)：521-525.
[104]胡飞,顾冬云,戴尅戎,等.基于非线性时间序列法研究人体步行稳定性[J].医用生物力学,2012,27(01)：51-57.
[105]彭志行,陶红,贾成梅,等.时间序列分析在麻疹疫情预测预警中的应用研究[J].中国卫生统计,2010,27(05)：459-463.
[106]张晗,王霞.基于小波分解的网络流量时间序列建模与预测[J].计算机应用研究,2012,29(08)：3134-3136.
[107]周芮锦,潘毅群,黄治钟.时间序列方法及其在实际办公楼能耗预测中的应用[J].建筑节能,2012,40(02)：55-59.
[108]杨淑莹,王丽贤,牛廷伟,等.基于粒子滤波优化的滚动式时间序列多步预测[J].系统工程与电子技术,2012,34(06)：1097-1101.
[109]李序颖,岳丹,顾岚.我国交通货物运输量的时间序列分析[J].系统工程理论与实践,2005,25(1)：49-55.
[110]许伦辉,唐德华,邹娜,等.基于非线性时间序列分析的短时交通流特性分析[J].重庆交通大学学报(自然科学版),2010,29(01)：110-113.
[111]田龙辉,苏厚勤,冯娟.时间序列分析在轨道交通客流预报中的应用研究[J].计算机应用与软件,2009,26(1)：176-177.
[112]韩超,宋苏,王成红.基于ARIMA模型的短时交通流实时自适应预测[J].系统仿真学报,2004,16(7)：1530-1532.
[113]邵辉,王钰,李保安,等.交通事故损失的时间序列分析[J].中国安全科学学报,2007,17(7)：10-13.
[114]王楠.山区高速公路危险品运输风险评价与安全保障系统[D].重庆：重庆交通大学,2011.
[115]姜昉.易燃气体泄漏扩散过程的数值模拟研究[D]：(硕士论文).北京：首都经济贸易大学,2008.
[116]李伟,汪佩兰.某LNG储罐蒸气云火灾爆炸数值模拟[J].北京理工大学学报,2003,23(4)：307-311.
[117]张彬,吴宛青.环境温度与风速对LNG船舶水下泄漏后果影响的数值研究[J].哈尔滨工程大学学报,2009,30(8)：855-859.
[118]张俊杰,陈安扬.危险品运输货舱通风的优化设计[J].上海造船,2008,(1)：44-46.
[119]温熙森.模式识别与状态监控[M].北京：科学出版社,2007.
[120]Nair H. A system for pattern recognition and pattern summarization in multi-band satellite images[J]. Pattern Recognition and Image Analysis,2008,18(1):43-57.
[121]Lapko A. V., Lapko V. A. Analysis of asymptotic properties of nonparametric estimate of the equation of the separation surface in a two-alternative problem of pattern recognition[J]. Optoelectronics, Instrumentation and Data Processing,2010,46(3):243-247.
[122]Goto Hiroomi, Konishi Tsuyoshi, Itoh Kazuyoshi. Efficiency improvement of optical pattern recognition in ultra-fast all-optical intensity equalizer[J]. Optical Review,2009,16(2):180-183.
[123]Mikhailov A. M. Pattern recognition by indexing[J]. Automation and Remote Control,2012, 73(4):717-724.
[124]Kosecka-Judin Ewa, Wesolowski Marek, Paukszta Dominik. Pattern recognition methods as supplementary techniques for identification of salicylamide - cyclodextrins inclusion complexes[J]. Central European Journal of Chemistry,2012,10(5):1534-1546.
[125]Neimark Yu. I., Teklina L. G. Possibilities of using pattern recognition methods in research on mathematical models[J]. Pattern Recognition and Image Analysis,2011,21(2):195-198.
[126]Mikhailov I. A. Some methods for pattern recognition[J]. Automatic Control and Computer Sciences,2010,44(7):420-425.
[127]Calcraft Lee, Maex Reinoud, Davey Neil, et al. The beneficial effects of non-specific synaptic plasticity for pattern recognition in auto-associative memory[J]. BMC Neuroscience,2011, 12(1):1-2.
[128]王志华.基于模式识别的柴油机故障诊断技术研究[D]：(博士论文).武汉：武汉理工大学,2004.
[129]潘巍,王阳生,杨宏戟.基于信息融合技术的集装箱号码自动识别系统[J].计算机工程,2007,33(04)：209-211.
[130]姚杰,任玉清,吴兆麟,等.多船会遇碰撞危险的模糊识别评价方法[J].大连水产学院学报,2002,17(1)：313-317.
[131]周晶洁.危险品运输与仓储[M].大连：大连海事大学出版社,2009.
[132]George E. P. Box Gwinlym M. Jenkins Gregory. TimeSeries Analysis:Forecasting and Control[M]. John Wiley,2008.
[133]轩建平,杨叔子,吴雅.时间序列分析的工程应用(第2版)[M].武汉：华中科技大学出版社,2007.
[134]王振龙.应用时间序列分析[M].第2版.北京：中国统计出版社,2010.
[135]魏武雄.时间序列分析-单变量和多变量方法[M].易丹辉,刘超,贺学强,译.北京：中国人民大学出版社,2009.
[136]刘次华.随机过程(第2版)[M].武汉：华中科技大学出版社,2006.
[137]陈灯塔.应用经济计量学：Eviews高级讲义(上、下册)[M].北京：北京大学出版社,2012.
[138]宋军,张宗新.金融计量学：基于SAS的金融实证研究[M].北京：北京大学出版社,2009.
[139]易丹辉.时间序列分析：方法与应用[M].北京：中国人民大学出版社,2011.
[140]鲜思东.概率论与数理统计[M].北京：科学出版社,2010.
[141]Anderson John D计算流体力学入门[M].姚朝晖,周强,译.北京：清华大学出版社,2010.
[142]李鹏飞,徐敏义,王飞飞.精通CFD工程仿真与案例实战-FLUENT GAMBIT ICEM CFD Tecplot[M]北京：人民邮电出版社,2011.
[143]李进良,李承曦,胡仁喜.精通FLUENT6.3流场分析[M].北京：化学工业出版社,2009.
[144]王福军.计算流体动力学分析-CFD软件原理与应用[M].北京：清华大学出版社,2004.
[145]吴德铭,郜冶.实用计算流体力学基础[M].哈尔滨：哈尔滨工程大学出版社,2006.
[146]汪增福.模式识别[M].合肥：中国科学技术大学出版社,2010.
[147]盛立东.模式识别导论[M].北京：北京邮电大学出版社,2010.
[148]李弼程,邵美珍,黄洁.模式识别原理与应用[M].西安：西安电子科技大学出版社,2008.
[149]孙即祥,姚伟,滕书华.模式识别[M].北京：国防工业出版社,2009.
[150]Haas Carl. A Model for Data Fusion in Civil Engineering[C].13th EG-ICE Workshop, Ascona, Switzerland,2006:315-319.
[151]Pande H., Tiwari PoonamS., Dobhal Shashi. Analyzing hyper-spectral and multi-spectral data fusion in spectral domain[J]. Journal of the Indian Society of Remote Sensing,2009,37(3):395-408.
[152]Zhong-hui Hu, Yun-zu Cai, Yuan-gui Li, et al. Data fusion for fault diagnosis using multi-class Support Vector Machines[J]. Journal of Zhejiang University Science A,2005, 6(10):1030-1039.
[153]Kim So-Ra, Kwak Doo-Ahn, Lee Woo-Kyun, et al. Erratum to:Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data[J]. Science China Life Sciences,2010,53(9):1162.
[154]Kalyana-Sundaram Shanker, Shanmugam Achiraman, Chinnaiyan ArulM. Gene Fusion Markup Language:a prototype for exchanging gene fusion data[J]. BMC Bioinformatics,2012, 13(1):1-8.
[155]Culler David, Estrin Deborah, Srivastava Mani. Guest Editors' Introduction:Overview of Sensor Networks[J]. Computer,2004,37(8):41-49.
[156]Wang Xiao-Jun, Yang Chen, Qiu Zhi-Ping. Non-probabilistic information fusion technique for structural damage identification based on measured dynamic data with uncertainty[J]. Acta Mechanica Sinica,2013,29(2):202-210.
[157]Mandic DaniloP., Goh SuLee, Aihara Kazuyuki. Sequential Data Fusion via Vector Spaces: Fusion of Heterogeneous Data in the Complex Domain[J]. The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology,2007,48(1-2):99-108.
[159]Brooks Alex, Williams Stefan. Tracking people with networks of heterogeneous sensors[C]. Proceedings of the Australasian Conference on Robotics and Automation, Australasian,2003:1-7.
[159]F Duarte M., Y Hen Hu. Vehicle classification in distributed sensor networks[J]. Journal of Parallel and Distributed Computing,2004,64(7):826-838.
[160]何友,王国宏,彭应宁.多传感器信息融合及应用(第2版)[M].北京：电子工业出版社,2010.
[161]SOMMER K. D., KUEHN O., LEON F. P., et al. A Bayesian approach to information fusion for evaluating the measurement uncertainty[J]. Robotics and Autonomous Systems,2009, 57(3):339-344.
[162]BASIR O.,YUAN Xiao hong. Engine fault diagnosis based on multi-sensor information fusion using dempster-shafer evidence theory[J]. Information Fusion,2007,8(4):379-386.
[163]高青.多传感器数据融合算法研究[D]：(硕士论文).西安：西安电子科技大学,2008.
[164]朱飞祥.远洋船舶调度数据挖掘技术研究与应用[D]：(博士论文).大连：大连海事大学,2008.
[165]申宇皓,孟晨,张磊,等.基于支持向量机的信息融合模拟电路故障诊断方法研究[J].计算机测量与控制,2009,17(11)：2177-2180.
[166]简小刚,贾鸿盛,石来德.多传感器信息融合技术的研究进展[J].中国工程机械学报.2009,7(2)：227-232.
[167]H. K Versteeg W. Malalasekera. An Introduction to Computational Fluid Dynamics:The Finite Volume Method[M]. New York:Wiley,1995.
[168]郭鸿志.传输过程数值模拟[M].北京：冶金工业出版社,1998.
[169]周雪漪.计算水力学[M].北京：清华大学出版社,1995.
[170]窦国仁.湍流力学[M].北京：高等教育出版社,1985.
[171]C Markatos N. The mathematical modeling of turbulence flows[J]. Apply Math Modeling, 1986(10):190-220.
[172]H Ferziger J. Computational methods for turbulent flows,transonic and viscous flows[M]. washington DC:Hemisphere,1983.
[173]Jordan S A Ragab S. A. A large eddy simulation near wake of a circular cylinder[J]. ASME J Fluids Engineering,1998(120):243-252.
[174]Kogaki T., Kobayashi T., Taniguchi N. Large eddy simulation of flow around a rectangular cylinder[J]. Fluid Dynamics Research,1997,20(1-6):11-24.
[175]Yang Z. Y. large eddy simulation of fully developed turbulent flow in a rotating pipe[J]. International journal for numerical methods in fluids,2000,33(5):681-694.
[176]陶文铨.计算传热学的近代进展[M].北京：科学出版社,2000.
[177]J Freitas C. Prospective:selected benchmarks from commercial CFD codes[J]. ASME J Fluids Engineering,1995,117(2):208-218.
[178]陶文铨.数值传热学(第二版)[M].西安：西安交通大学出版社,2001.
[179]Inc. Fluent. Fluent User's Guide[M]. Fluent Inc.,2003.
[180]J Lin M., W Wang Q., Q Tao W. Developing laminar flow and heat transfer in annular-sector ducts[J]. Heat transfer engineering,2000,21(2):53-61.
[181]B Wang L., D Jiang G., Q Tao W. Numerical simulation on heat transfer and fluid flow characteristics of arrays with nonuniform plate length positioned obliquely to the flow direction[J]. Journal of heat transf,1998,120(4):991-998.
[182]Yuan Z X, Tao W Q, Wang Q W. Numerical prediction for laminar forced convection heat transfer in parallel-plate channels with stream wise-periodic rod disturbances[J]. International journal for numerical methods in fluids,1998,28(9):1371-1387.
[183]Wang Q W, Wei J G, Tao W Q. An improved numerical algorithm for solution of convective heat transfer problems on nonstaggered grid system[J]. Heat and Mass Transfer,1998, 4(33):273-280.
[184]Wang L B, Tao W Q. Numerical analysis on heat transfer and fluid flow for arrays of non-uniform plate length aligned at angles to the flow direction[J]. International Journal of Numerical Methods for Heat & Fluid Flow,1997,7(5):479-496.
[185]柯斯乐E.L.扩散：流体系统中的传质[M].北京：化学工业出版社,2002.
[186]Fayyad U M Piatetsky-Shapiro G. Smyth P. Advances in knowledge discovery and data mining[M]. Menlo Park:AAAI Press,1996.
[187]Berndt D Clifford J. Using dynamic time warping to find patterns in time series[C]. KDD workshop, Washington,1994:359-370.
[2]http://www.shmsa.gov.cn/NewsContent.aspx?CatalogId=4a6ef228-096d-444d-9194-af328c73f7 61 & Content Id=1376291e-8bb1-4848-8755-8f5aec381f42 [EB/OL].
[3]Lee K, Ni S. On the dynamic effects of oil price shocks:a study using industry level data[J]. Journal of Monetary Economics,2002,49(4):823-852.
[4]Atkeson A, Kehoe P J. Models of energy use:Putty-putty versus putty-clay[J]. The American Economic Review,1999,89(4):1028-1043.
[5]Webb I R, Larson R C. Period and phase of customer replenishment:A new approach to the strategic inventory/routing problem[J]. European Journal of Operational Research,1995,85(1): 132-148.
[6]刘庆华.基于现金流量的企业财务预警系统研究[D]：(博士论文).成都：西南财经大学,2006.
[7]冯征.数据挖掘方法在财务预警中的应用研究[D]：(博士论文).天津：天津大学,2007.
[8]鄢志娟.基于现金流量的企业财务危机预警系统分析[J].改革与战略,2008,24(8)：144-147.
[9]Mitchell J V. A new political economy of oil[J]. The Quarterly Review of Economics and Finance,2002,42(2):251-272.
[10]Bentley R W. Global oil & gas depletion:an overview[J]. Energy policy,2002,30(3):189-205.
[11]袁志祥,单修政,徐世芳,等.地震预警技术综述[J].自然灾害学报,2007,16(6)：216-223.
[12]唐晓纯,苟变丽.食品安全预警体系框架构建研究[J].食品科学,2005,26(12)：246-250.
[13]李万莲.我国生态安全预警研究进展[J].安全与环境工程,2008,15(03)：78-81.
[14]曹明贵,马海.构建城镇贫困人口的预警机制模型[J].信阳师范学院学报：哲学社会科学版,2011,31(001)：37-41.
[15]佘丛国,席酉民.我国企业预警研究理论综述[J].预测,2003,2(003)：23-29.
[16]李明.城市房地产预警技术研究[J].数理统计与管理,2006,25(3)：315-320.
[17]黄礼,李万超.主成分分析法在财务预警实证研究中的应用[J].统计与信息论坛,2003,18(5)：83-86.
[18]陈虎虎,钟方平,许学忠,等.基于支持向量机的低空飞行目标声识别[J].系统工程与电子技术,2005,27(1)：46-48.
[19]韩郁葱,郜兵.模糊综合评判在设备故障预警专家系统中的应用[J].合肥工业大学学报(自然科学版),2007,30(6)：746-749.
[20]史成东,边敦新,苏菊宁.基于粗糙集和灰色的供应链知识共享风险预警[J].计算机工程与应用,2008,44(11)：19-22.
[21]马祖长,孙怡宁,梅涛.无线传感器网络综述[J].通信学报,2004,25(4)：114-124.
[22]倪明选,刘云浩,朱燕民.无线传感网络的基础理论及关键技术研究[J].中国基础科学,2008,10(1)：24-28.
[23]叶嘉.设备监控无线传感器网络路由协议的设计与实现[D]：(硕士论文).长沙：国防科技大学,2006.
[24]何思远.基于无线传感器网络的瓦斯监测系统的研究[D]：(硕士论文).昆明：昆明理工大学,2007.
[25]张坚林.基于无线传感器网络的远程健康监控应用研究[D]：(硕士论文).南昌大学,2007.
[26]陈斌,万江文,冯仁剑,等.基于WSN的高速公路监控系统智能化研究[J].微纳电子技术,2007,44(7)：442-445.
[27]Mou Ruifang. Environmental risk assessment model on dangerous goods during transportation [C].2010 8th International Conference on Supply Chain Management and Information Systems (SCMIS), Hong Kong.2010:1-5.
[28]Erkut Erhan, Ingolfsson Armann. Transport risk models for hazardous materials:revisited[J]. Operations Research Letters,2005,33(1):81-89.
[29]Li Rongrong, Leung Yee. Multi-objective route planning for dangerous goods using compromise programming[J]. Journal of Geographical Systems,2011,13(3):249-271.
[30]Erhan Erkut Vedat Veter. Modeling of transport risk for hazardous materials[J]. Operations Research,1998,46(5):625-642.
[31]高清平.不确定条件下危险货物公路运输风险分析、路径选择与网络优化研究[D]：(博士论文).成都：西南交通大学,2010.
[32]黄森.危险品运输风险评价体系及路径选择研究[D]：(硕士论文).沈阳：沈阳工业大学2010.
[33]Xuesong Cai, Junwei Wu. Hazardous Chemicals Vehicles Rollover Pre-warning System Based on CPS[C].2012 IEEE Sixth International Conference on Software Security and Reliability Companion (SERE-C), Gaithersburg, MD,2012:184-187.
[34]王云鹏,孙文财,隗海林,等.基于侧倾的运输液态危险化学品的罐式半挂汽车危险状态辨识[J].吉林大学学报(工学版),2010,40(03)：640-644.
[35]陶存新,严新平,刘清.危险品运输预警应急联动机制研究[J].武汉理工大学学报(交通科学与工程版),2007,(06)：980-983.
[36]陶存新.危险品运输预警应急指挥系统研究[D]：(博士论文).武汉：武汉理工大学,2007.
[37]郝连胜.危险化学品罐式集装箱公路运输风险评价研究[D]：(硕士论文).上海：上海海事大学,2007.
[38]尹晋.气体类危险货物道路运输风险评价研究[D]：(硕士论文).北京：北京交通大学,2012.
[39]尚鸿雁,董千里,王旭坪,等.基于Fuzzy AHP的危险货物运输风险评估与预警[J].长安大学学报(社会科学版),2009,11(01)：21-27.
[40]郭培杰,蒋军成.模糊综合评价法在危险化学品道路运输风险评价中的应用[J].南京工业大学学报(自然科学版),2006,(05)：57-62.
[41]Cheng Jie, Wen Chao. Risk assessment model approach for dangerous goods transported by railway[J]. Journal of Transportation Security,2011,4(4):351-359.
[42]肖金梅,帅斌.铁路危险货物运输风险定量研究[J].铁道运输与经济,2010,32(10)：66-69.
[43]罗帆,刘英.机场危险品事故的预警管理体系探讨[J].武汉理工大学学报(社会科学版),2007(04)：421-424.
[44]王永刚,朱迪.航空危险品运输作业风险管理[J].中国安全生产科学技术,2012,8(07)：180-184.
[45]聂燕.航空危险品运输风险评价研究[D]：(硕士论文).成都：电子科技大学,2010.
[46]张伟.浅议危险品水路运输预警管理[J].中国水运(下半月),2010,10(07)：37-38.
[47]Donk J., de Rijke W. G. A risk-effect model for waterway transport of dangerous goods[C]. Reliability and Maintainability Symposium, Washington, DC,1995:349-355.
[48]Yu Bin, Jin Yongxing, Xiao Ying Jie, et al. Evaluation of maritime hazadous cargo transportation[C].2010 International Conference on Computer Application and System Modeling (ICCASM), Taiyuan, China,2010:438-441.
[49]王军,褚艳玲.基于模糊综合评价法的水路危险化学品运输风险评价[J].大连海事大学学报,2008,34(S1)：14-16.
[50]茅家源.危险货物水路运输预警管理研究[D]：(硕士论文).南京：南京理工大学,2008.
[51]李明珂.液化气船航运过程中的综合安全评价研究[D]：(硕士论文).大连：大连海事大学,2006.
[52]俞斌,金永兴,郑滨,等.基于证据理论的散装液体化学品船安全评估[J].中国航海,2012,35(01)：90-93.
[53]俞斌.不确定条件下散装液体化学品船安全评价方法及应用研究[D]：(博士论文).上海：上 海海事大学,2011.
[54]Lee Jae-Ho. A Traffic-Aware Energy Efficient Scheme for WSN Employing an Adaptable Wakeup Period[J]. Wireless Personal Communications,2012,7(3):1879-1914.
[55]Xu Xiaorong, Zhang Jianwu, Huang Aiping, et al. An adaptive measurement scheme based on compressed sensing for wideband spectrum detection in cognitive WSN[J]. Journal of Electronics (China),2012,29(6):585-592.
[56]Wang WenJie, Yao BoBin, Yin QinYe. AOD estimation in WSN localization system with synthetic aperture technique[J]. Science China Information Sciences,2012,55(10):2216-2225.
[57]Wu Guowei, Lin Chi, Yao Lin, et al. A cluster based WSN fault tolerant protocol[J]. Journal of Electronics (China),2010,27(1):43-50.
[58]Padilla P., Camacho J., Macia-Fernandez G., etal. Erratum to:On the Influence of the Propagation Channel in the Performance of Energy-Efficient Geographic Routing Algorithms for Wireless Sensor Networks (WSN)[J]. Wireless Personal Communications,2013,70(1):39.
[59]Aoun Bassam, Boutaba Raouf. Clustering in WSN with Latency and Energy Consumption Constraints[J]. Journal of Network and Systems Management,2006,14(3):415-439.
[60]Popov A. L., Vendik O. G., Zubova N. A. Magnetic field intensity in near field zone of loop antenna for RFID systems[J]. Technical Physics Letters,2010,36(10):882-884.
[61]Gu Qing-hua, Lu Cai-wu, Li Fa-ben, et al. Mining production information management system in an open pit based on GIS/GPS/GPRS/RFID[J]. Journal of Coal Science and Engineering (China), 2010,16(2):176-181.
[62]Escribano JavierG., Garcia Andres. Human condition monitoring in hazardous locations using pervasive RFID sensor tags and energy-efficient wireless networks[J]. Journal of Zhejiang University SCIENCE,2012,13(9):674-688.
[63]He Yejun. Study of Magnetic Field Coupling Technologies in Activating RFID-SIM Card Mobile Payments[J]. Wireless Personal Communications,2012:1-12.
[64]Boccadoro Mauro, Martinelli Francesco, Pagnottelli Stefano. Constrained and quantized Kalman filtering for an RFID robot localization problem[J]. Autonomous Robots,2010, 29(3-4):235-251.
[65]Luo Zhiyong, Jiang Jing, Wang Ping. Enhanced energy-saving anticollision algorithms with improving throughput for RFID system[J]. Journal of Electronics (China),2013,30(1):40-48.
[66]Merentitis A., Kranitis N., Paschalis A., et al. Low Energy Online Self-Test of Embedded Processors in Dependable WSN Nodes[J]. Dependable and Secure Computing,2012,9(1):86-100.
[67]Otero C. E., Shaw W. H., Kostanic I., et al. Multiresponse Optimization of Stochastic WSN Deployment Using Response Surface Methodology and Desirability Functions[J]. Systems Journal, 2010,4(l):39-48.
[68]Meng-Shiuan Pan, Lun-Wu Yeh, Yen-Ann Chen, et al. A WSN-Based Intelligent Light Control System Considering User Activities and Profiles[J]. Sensors Journal,2008,8(10):1710-1721.
[69]Rida A., Li Yang, Vyas R., et al. Conductive Inkjet-Printed Antennas on Flexible Low-Cost Paper-Based Substrates for RFID and WSN Applications[J]. Antennas and Propagation Magazine, 2009,51(3):13-23.
[70]Alippi C., Camplani R., Galperti C., et al. A Robust, Adaptive, Solar-Powered WSN Framework for Aquatic Environmental Monitoring[J], Sensors Journal,2011,11(1):45-55.
[71]方来华,刘骥,魏利军,等.危险品运输车辆监控预警系统设计与开发[J].中国安全科学学报,2008,18(05)：109-115.
[72]周受钦,段战归.危险化学品运输罐式装备智能监测系统[J].集装箱化,2007(11)：10-12.
[73]张令勇,高松,钟磊,等.基于3G的危险品车辆在途监控预警系统的设计[J].山东理工大学学报(自然科学版),2010,24(01)：70-74.
[74]周军.基于GPS/GPRS/GIS的危险品运输监控系统研究与设计[D]：(硕士论文).西安：长安大学,2007.
[75]徐蓉.基于GPS/GPRS/RFID的危险品车辆监控系统的研究[D]：(硕士论文).上海：上海海事大学,2007.
[76]程志端.基于多传感器的危险品运输监控系统研究与实现[D]：(硕士论文).武汉：武汉理工大学,2011.
[77]Valente F., Zacheo G., Losito P., et al. A telecommunications framework for real-time monitoring of dangerous goods transport[C].2009 9th International Conference on Intelligent Transport Systems Telecommunications(ITST),Lille,2009:13-18.
[78]张兵,李士宁,蒋思佳,等.基于WSNs的危险品车辆在途监测预警系统[J].计算机测量与控制,2012,20(03)：630-633.
[79]鞠迎华.基于WSN和RFID的铁路危险品在途监测技术研究与实现[D]：(硕士论文).北京：北京交通大学,2012.
[80]张志华,许开立.基于物联网技术危险品运输车辆智能监控系统的设计[C].2012(沈阳)国际安全科学与技术学术研讨会,中国辽宁沈阳,2012：68-75.
[81]王开乐,钟慧玲,张智勇.基于RFID/GPS/GPRS危险品运输管理系统的研究[J].物流技术,2009,8(04)：133-135.
[82]陈春贻,朱云,黎嘉明,等.危险品运输实时监控及应急救援服务平台构建[J].中国安全科学学报,2009,19(06)：109-115.
[83]Xu Peng. Ship cabin environment monitoring system based on wireless sensor network[C]. World Automation Congress (WAC), Puerto Vallarta, Mexico,2012:1-4.
[84]Zhang Yingjun, Xing Shengwei, Xu Peng, et al. Shipping containers of dangerous goods condition monitoring system based on wireless sensor network[C].2010 6th International Conference on Networked Computing (INC), Gyeongju,2010:1-3.
[85]周园,肖洪祥,董俊飞.基于MATLAB的太阳黑子时间序列分析与仿真[J].网络安全技术与应用,2012(03)：26-28.
[86]缪海波,殷坤龙,柴波,等.基于非平稳时间序列分析的滑坡变形预测[J].地质科技情报,2009,28(04)：107-111.
[87]邓继辉,陈柏林.基于时间序列分析的滑坡变形动态预测研究[J].长江科学院院报,2012,29(10)：78-81.
[88]柴微涛,宋述军,宋学鸿.成都市城区空气污染指数的时间序列分析[J].成都理工大学学报(自然科学版),2007,(04)：485-488.
[89]李冬,周川,袁朋飞,等.基于时间序列分析的渐变性水源水质预测研究[J].环境科学与技术,2012,35(06)：184-188.
[90]卢文喜,杨磊磊,龚磊,等.基于时间序列分析改进法的地下水位动态预报——以吉林省桦甸市为例[J].吉林大学学报(地球科学版),2012,42(S1)：367-372.
[91]朱睿,张俊中,龙洋,等.时间序列模型在建筑物沉降监测中的应用[J].测绘与空间地理信息,2012,35(02)：213-216.
[92]王晓鹏,曹广超,丁生喜.基于Box-Jenkins方法的青南高原降水量时间序列分析建模与预测[J].数理统计与管理,2008(04)：565-570.
[93]李东福,董雷,礼晓飞,等.基于多尺度小波分解和时间序列法的风电场风速预测[J].华北电力大学学报(自然科学版),2012,39(02)：43-48.
[94]丁明,张立军,吴义纯.基于时间序列分析的风电场风速预测模型[J].电力自动化设备,2005,(08)：32-34.
[95]刘辉,田红旗,李燕飞.基于小波分析法与滚动式时间序列法的风电场风速短期预测优化算法[J].中南大学学报(自然科学版),2010,41(01)：370-375.
[96]杨磊磊,卢文喜,刘派,等.时间序列分析及Monte Carlo方法在降水预报中的应用[J].环境科学与技术,2011,34(05)：108-112.
[97]潘雅婧,王仰麟,彭建,等.基于小波与R/S方法的汉江中下游流域降水量时间序列分析[J].地理研究,2012,31(05)：811-820.
[98]徐方舟,宋现锋,马灵玲,等.基于DEMETER卫星观测数据的电离层离子温度时间序列 预测模型[J].遥感信息,2012(02)：25-30.
[99]王毅,赵建军,付龙文,等.基于时间序列的GPS定位误差分析[J].现代科学仪器,2012,(02)：45-49.
[100]武文华,付和平,武晓东,等.应用时间序列分析法预测黑线仓鼠和长爪沙鼠种群数量[J].内蒙古农业大学学报(自然科学版),2007(04)：6-11.
[101]蒙玉波.时间序列分析在居民消费水平指数预测中的应用[J].广西师范学院学报(自然科学版),2012,29(01)：37-44.
[102]甘小冰,陶大俊.基于小波时间序列分析的电子银行风险预测[J].现代电子技术,2012,35(15)：70-71.
[103]殷文军,彭晓武,宋世震,等.广州市空气污染与城区居民心脑血管疾病死亡的时间序列分析[J].环境与健康杂志,2012,29(06)：521-525.
[104]胡飞,顾冬云,戴尅戎,等.基于非线性时间序列法研究人体步行稳定性[J].医用生物力学,2012,27(01)：51-57.
[105]彭志行,陶红,贾成梅,等.时间序列分析在麻疹疫情预测预警中的应用研究[J].中国卫生统计,2010,27(05)：459-463.
[106]张晗,王霞.基于小波分解的网络流量时间序列建模与预测[J].计算机应用研究,2012,29(08)：3134-3136.
[107]周芮锦,潘毅群,黄治钟.时间序列方法及其在实际办公楼能耗预测中的应用[J].建筑节能,2012,40(02)：55-59.
[108]杨淑莹,王丽贤,牛廷伟,等.基于粒子滤波优化的滚动式时间序列多步预测[J].系统工程与电子技术,2012,34(06)：1097-1101.
[109]李序颖,岳丹,顾岚.我国交通货物运输量的时间序列分析[J].系统工程理论与实践,2005,25(1)：49-55.
[110]许伦辉,唐德华,邹娜,等.基于非线性时间序列分析的短时交通流特性分析[J].重庆交通大学学报(自然科学版),2010,29(01)：110-113.
[111]田龙辉,苏厚勤,冯娟.时间序列分析在轨道交通客流预报中的应用研究[J].计算机应用与软件,2009,26(1)：176-177.
[112]韩超,宋苏,王成红.基于ARIMA模型的短时交通流实时自适应预测[J].系统仿真学报,2004,16(7)：1530-1532.
[113]邵辉,王钰,李保安,等.交通事故损失的时间序列分析[J].中国安全科学学报,2007,17(7)：10-13.
[114]王楠.山区高速公路危险品运输风险评价与安全保障系统[D].重庆：重庆交通大学,2011.
[115]姜昉.易燃气体泄漏扩散过程的数值模拟研究[D]：(硕士论文).北京：首都经济贸易大学,2008.
[116]李伟,汪佩兰.某LNG储罐蒸气云火灾爆炸数值模拟[J].北京理工大学学报,2003,23(4)：307-311.
[117]张彬,吴宛青.环境温度与风速对LNG船舶水下泄漏后果影响的数值研究[J].哈尔滨工程大学学报,2009,30(8)：855-859.
[118]张俊杰,陈安扬.危险品运输货舱通风的优化设计[J].上海造船,2008,(1)：44-46.
[119]温熙森.模式识别与状态监控[M].北京：科学出版社,2007.
[120]Nair H. A system for pattern recognition and pattern summarization in multi-band satellite images[J]. Pattern Recognition and Image Analysis,2008,18(1):43-57.
[121]Lapko A. V., Lapko V. A. Analysis of asymptotic properties of nonparametric estimate of the equation of the separation surface in a two-alternative problem of pattern recognition[J]. Optoelectronics, Instrumentation and Data Processing,2010,46(3):243-247.
[122]Goto Hiroomi, Konishi Tsuyoshi, Itoh Kazuyoshi. Efficiency improvement of optical pattern recognition in ultra-fast all-optical intensity equalizer[J]. Optical Review,2009,16(2):180-183.
[123]Mikhailov A. M. Pattern recognition by indexing[J]. Automation and Remote Control,2012, 73(4):717-724.
[124]Kosecka-Judin Ewa, Wesolowski Marek, Paukszta Dominik. Pattern recognition methods as supplementary techniques for identification of salicylamide - cyclodextrins inclusion complexes[J]. Central European Journal of Chemistry,2012,10(5):1534-1546.
[125]Neimark Yu. I., Teklina L. G. Possibilities of using pattern recognition methods in research on mathematical models[J]. Pattern Recognition and Image Analysis,2011,21(2):195-198.
[126]Mikhailov I. A. Some methods for pattern recognition[J]. Automatic Control and Computer Sciences,2010,44(7):420-425.
[127]Calcraft Lee, Maex Reinoud, Davey Neil, et al. The beneficial effects of non-specific synaptic plasticity for pattern recognition in auto-associative memory[J]. BMC Neuroscience,2011, 12(1):1-2.
[128]王志华.基于模式识别的柴油机故障诊断技术研究[D]：(博士论文).武汉：武汉理工大学,2004.
[129]潘巍,王阳生,杨宏戟.基于信息融合技术的集装箱号码自动识别系统[J].计算机工程,2007,33(04)：209-211.
[130]姚杰,任玉清,吴兆麟,等.多船会遇碰撞危险的模糊识别评价方法[J].大连水产学院学报,2002,17(1)：313-317.
[131]周晶洁.危险品运输与仓储[M].大连：大连海事大学出版社,2009.
[132]George E. P. Box Gwinlym M. Jenkins Gregory. TimeSeries Analysis:Forecasting and Control[M]. John Wiley,2008.
[133]轩建平,杨叔子,吴雅.时间序列分析的工程应用(第2版)[M].武汉：华中科技大学出版社,2007.
[134]王振龙.应用时间序列分析[M].第2版.北京：中国统计出版社,2010.
[135]魏武雄.时间序列分析-单变量和多变量方法[M].易丹辉,刘超,贺学强,译.北京：中国人民大学出版社,2009.
[136]刘次华.随机过程(第2版)[M].武汉：华中科技大学出版社,2006.
[137]陈灯塔.应用经济计量学：Eviews高级讲义(上、下册)[M].北京：北京大学出版社,2012.
[138]宋军,张宗新.金融计量学：基于SAS的金融实证研究[M].北京：北京大学出版社,2009.
[139]易丹辉.时间序列分析：方法与应用[M].北京：中国人民大学出版社,2011.
[140]鲜思东.概率论与数理统计[M].北京：科学出版社,2010.
[141]Anderson John D计算流体力学入门[M].姚朝晖,周强,译.北京：清华大学出版社,2010.
[142]李鹏飞,徐敏义,王飞飞.精通CFD工程仿真与案例实战-FLUENT GAMBIT ICEM CFD Tecplot[M]北京：人民邮电出版社,2011.
[143]李进良,李承曦,胡仁喜.精通FLUENT6.3流场分析[M].北京：化学工业出版社,2009.
[144]王福军.计算流体动力学分析-CFD软件原理与应用[M].北京：清华大学出版社,2004.
[145]吴德铭,郜冶.实用计算流体力学基础[M].哈尔滨：哈尔滨工程大学出版社,2006.
[146]汪增福.模式识别[M].合肥：中国科学技术大学出版社,2010.
[147]盛立东.模式识别导论[M].北京：北京邮电大学出版社,2010.
[148]李弼程,邵美珍,黄洁.模式识别原理与应用[M].西安：西安电子科技大学出版社,2008.
[149]孙即祥,姚伟,滕书华.模式识别[M].北京：国防工业出版社,2009.
[150]Haas Carl. A Model for Data Fusion in Civil Engineering[C].13th EG-ICE Workshop, Ascona, Switzerland,2006:315-319.
[151]Pande H., Tiwari PoonamS., Dobhal Shashi. Analyzing hyper-spectral and multi-spectral data fusion in spectral domain[J]. Journal of the Indian Society of Remote Sensing,2009,37(3):395-408.
[152]Zhong-hui Hu, Yun-zu Cai, Yuan-gui Li, et al. Data fusion for fault diagnosis using multi-class Support Vector Machines[J]. Journal of Zhejiang University Science A,2005, 6(10):1030-1039.
[153]Kim So-Ra, Kwak Doo-Ahn, Lee Woo-Kyun, et al. Erratum to:Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data[J]. Science China Life Sciences,2010,53(9):1162.
[154]Kalyana-Sundaram Shanker, Shanmugam Achiraman, Chinnaiyan ArulM. Gene Fusion Markup Language:a prototype for exchanging gene fusion data[J]. BMC Bioinformatics,2012, 13(1):1-8.
[155]Culler David, Estrin Deborah, Srivastava Mani. Guest Editors' Introduction:Overview of Sensor Networks[J]. Computer,2004,37(8):41-49.
[156]Wang Xiao-Jun, Yang Chen, Qiu Zhi-Ping. Non-probabilistic information fusion technique for structural damage identification based on measured dynamic data with uncertainty[J]. Acta Mechanica Sinica,2013,29(2):202-210.
[157]Mandic DaniloP., Goh SuLee, Aihara Kazuyuki. Sequential Data Fusion via Vector Spaces: Fusion of Heterogeneous Data in the Complex Domain[J]. The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology,2007,48(1-2):99-108.
[159]Brooks Alex, Williams Stefan. Tracking people with networks of heterogeneous sensors[C]. Proceedings of the Australasian Conference on Robotics and Automation, Australasian,2003:1-7.
[159]F Duarte M., Y Hen Hu. Vehicle classification in distributed sensor networks[J]. Journal of Parallel and Distributed Computing,2004,64(7):826-838.
[160]何友,王国宏,彭应宁.多传感器信息融合及应用(第2版)[M].北京：电子工业出版社,2010.
[161]SOMMER K. D., KUEHN O., LEON F. P., et al. A Bayesian approach to information fusion for evaluating the measurement uncertainty[J]. Robotics and Autonomous Systems,2009, 57(3):339-344.
[162]BASIR O.,YUAN Xiao hong. Engine fault diagnosis based on multi-sensor information fusion using dempster-shafer evidence theory[J]. Information Fusion,2007,8(4):379-386.
[163]高青.多传感器数据融合算法研究[D]：(硕士论文).西安：西安电子科技大学,2008.
[164]朱飞祥.远洋船舶调度数据挖掘技术研究与应用[D]：(博士论文).大连：大连海事大学,2008.
[165]申宇皓,孟晨,张磊,等.基于支持向量机的信息融合模拟电路故障诊断方法研究[J].计算机测量与控制,2009,17(11)：2177-2180.
[166]简小刚,贾鸿盛,石来德.多传感器信息融合技术的研究进展[J].中国工程机械学报.2009,7(2)：227-232.
[167]H. K Versteeg W. Malalasekera. An Introduction to Computational Fluid Dynamics:The Finite Volume Method[M]. New York:Wiley,1995.
[168]郭鸿志.传输过程数值模拟[M].北京：冶金工业出版社,1998.
[169]周雪漪.计算水力学[M].北京：清华大学出版社,1995.
[170]窦国仁.湍流力学[M].北京：高等教育出版社,1985.
[171]C Markatos N. The mathematical modeling of turbulence flows[J]. Apply Math Modeling, 1986(10):190-220.
[172]H Ferziger J. Computational methods for turbulent flows,transonic and viscous flows[M]. washington DC:Hemisphere,1983.
[173]Jordan S A Ragab S. A. A large eddy simulation near wake of a circular cylinder[J]. ASME J Fluids Engineering,1998(120):243-252.
[174]Kogaki T., Kobayashi T., Taniguchi N. Large eddy simulation of flow around a rectangular cylinder[J]. Fluid Dynamics Research,1997,20(1-6):11-24.
[175]Yang Z. Y. large eddy simulation of fully developed turbulent flow in a rotating pipe[J]. International journal for numerical methods in fluids,2000,33(5):681-694.
[176]陶文铨.计算传热学的近代进展[M].北京：科学出版社,2000.
[177]J Freitas C. Prospective:selected benchmarks from commercial CFD codes[J]. ASME J Fluids Engineering,1995,117(2):208-218.
[178]陶文铨.数值传热学(第二版)[M].西安：西安交通大学出版社,2001.
[179]Inc. Fluent. Fluent User's Guide[M]. Fluent Inc.,2003.
[180]J Lin M., W Wang Q., Q Tao W. Developing laminar flow and heat transfer in annular-sector ducts[J]. Heat transfer engineering,2000,21(2):53-61.
[181]B Wang L., D Jiang G., Q Tao W. Numerical simulation on heat transfer and fluid flow characteristics of arrays with nonuniform plate length positioned obliquely to the flow direction[J]. Journal of heat transf,1998,120(4):991-998.
[182]Yuan Z X, Tao W Q, Wang Q W. Numerical prediction for laminar forced convection heat transfer in parallel-plate channels with stream wise-periodic rod disturbances[J]. International journal for numerical methods in fluids,1998,28(9):1371-1387.
[183]Wang Q W, Wei J G, Tao W Q. An improved numerical algorithm for solution of convective heat transfer problems on nonstaggered grid system[J]. Heat and Mass Transfer,1998, 4(33):273-280.
[184]Wang L B, Tao W Q. Numerical analysis on heat transfer and fluid flow for arrays of non-uniform plate length aligned at angles to the flow direction[J]. International Journal of Numerical Methods for Heat & Fluid Flow,1997,7(5):479-496.
[185]柯斯乐E.L.扩散：流体系统中的传质[M].北京：化学工业出版社,2002.
[186]Fayyad U M Piatetsky-Shapiro G. Smyth P. Advances in knowledge discovery and data mining[M]. Menlo Park:AAAI Press,1996.
[187]Berndt D Clifford J. Using dynamic time warping to find patterns in time series[C]. KDD workshop, Washington,1994:359-370.