| 基于证据理论和可变模糊集的成都市洪灾风险评估 |
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| 引用本文： | 任玉峰,刘国东,周理,张春敏.基于证据理论和可变模糊集的成都市洪灾风险评估[J].农业工程学报,2014,30(21):147-156. |
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| 作者姓名： | 任玉峰 刘国东 周理 张春敏 |
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| 作者单位： | 1. 四川大学水利水电学院,成都,610065
2. 四川大学水利水电学院，成都 610065; 四川大学水力学与山区河流开发保护国家重点实验室，成都 610065 |
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| 基金项目： | 国家自然科学基金青年基金项目（51209152） |
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| 摘 要： | 洪灾系统的高维性和不确定性,给灾害风险评估带来较多困难,为了提高评估的准确性和合理性,实现科学灾害管理,该文将Dempster_Shafer证据理论应用到洪水灾害风险评估中,同时利用可变模糊集理论来构造证据理论基本信任分配,实现了客观合理的证据建模,最后利用经典组合原理进行证据组合。以成都市区2012年风险等级的计算为例,风险为高等级时的信任区间为0,0.52],似然区间为0,0.54],不确定大小为0.019,根据判断规则,确定市区2012年的洪灾风险等级为高。基于此方法采用相同处理,对研究区成都市风险等级的时空分布进行了计算分析。结果表明该方法能够较好地融合洪水灾害系统各方面信息以及处理风险评估中的不确定性,实现了洪灾风险的准确评估。
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| 关 键 词： | 洪水灾害 风险评估 模糊集 Dempster-Shafer证据理论 可变模糊集 不确定性 |
| 收稿时间： | 2014/5/14 0:00:00 |
| 修稿时间： | 2014/10/7 0:00:00 |
Risk evaluation of Chengdu's flood hazard based on evidence theory and variable fuzzy sets theory |
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| Ren Yufeng,Liu Guodong,Zhou Li and Zhang Chunmin.Risk evaluation of Chengdu's flood hazard based on evidence theory and variable fuzzy sets theory[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(21):147-156. |
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| Authors: | Ren Yufeng Liu Guodong Zhou Li and Zhang Chunmin |
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| Institution: | 1. College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China;1. College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China2. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China;1. College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China;1. College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China |
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| Abstract: | Abstract: Under the background of global climate change, the sustainable development of a society is extraordinarily endangered by the growing frequent and severe flood in China. Flood hazard is a highly uncertain and high-dimensional system. Thus, more difficulties emerge when carrying out flood risk evaluation. In this paper, the Dempster-Shafer (DS) evidence theory was applied to evaluate the flood hazard risk due to its ability in multisource information fusing and information uncertainty processing. The establishment of basic belief assignment (BBA) called evidence model is the nodus and hotspot in DS evidence theory research. In order to solve this problem, BBA was established and combined with comprehensive relative membership degree of index by using variable fuzzy sets theory (VFS). More specifically, the value of BBA was assigned by relatively comprehensive membership degree of VFS theory during the calculation process. BBA of hazard-formative environment, disaster-inducing factors and hazard bearing body were seen as the three pieces of evidence, and these evidences were combined by the classical evidence combination principle. Then, the decisions of flood disaster risk assessment were made by comparing quality function, belief function, relief function and uncertainty of each risk degree. So far, the objective and reasonable evidence model was established in this way while the conflict evidence was greatly reduced. Through evidence combination and the calculation of confidence, likelihood and uncertain interval of different risk degrees based on the classic evidence combination principle, the flood hazard risk was accurately assessed. The DS_VFS model was applied to evaluate the flood hazard risk in Cheng Du where flood disaster has been serious since ancient times. The study area was divided into 12 partitions and each subarea's hazard risk degree was calculated respectively by using DS_VFS model. The results indicated that the risk degree of Cheng Du was high, especially in the northwest, northeast and southwest. According to the spatial and time analysis, the risk growth was mainly due to three factors, increase in population, lagging infrastructure in economic development and continuous deterioration of the natural environment. In order to verify the DS-VFS model, the same historical flood data, altitude and slope data, rainfall data series and socioeconomic data were used in VFS theory, and the result was compared with the flood risk degrees calculated by DS-VFS. The comparison showed that the results of the DS_VFS model were more accurate and accorded better with the actual situation than the VFS results. The multidimensional information of social, economic and natural environment was fused, and uncertain interval of different degrees was calculated. Moreover, the purpose of accurate assessment of flood disaster risk in the study area was achieved by using the DS_VFS model, which was developed from the traditional fuzzy model. However, there were some problems that remain unaddressed in the current study. The conflict evidence was greatly reduced by calculating relative-membership grades, but it was not totally avoided. Besides, wrong decisions can be produced based on the classic evidence combination principle where the conflict evidence was high. In addition, many other calculation methods and decision fusion theories are available to be introduced into the DS_VFS model in the future research, such as support vector machine, absorption method, evidence distance function based on confidence, etc. |
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| Keywords: | flood damage risk assessment fuzzy sets Dempster-Shafer evidence theory variable fuzzy sets uncertainty |
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