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Fuzzy approach in the uncertainty analysis of the water distribution network of Becej

机译:Becej供水管网不确定性分析的模糊方法

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摘要

One of the most important steps in the development of water distribution system simulation models is providing the dependence of results of simulation on the uncertainty of input values. Information about propagation of uncertainty through the simulation model provides a basis for general model improvement in an efficient and economic (low cost) way. Besides statistically based uncertainty and sensitivity analyses, the fuzzy set theory provides an alternative that does not require crisp statistical measures of input parameter distributions. Uncertainty is represented by fuzzy set parameters, which do not have direct correspondence with statistical background, although indications of uncertainty can be easily recognized. In the analysis presented in this article, applied to the model water distribution system of the Becej community, roughness of old pipes has been selected as the uncertain parameter, as the correct values and their statistical distribution are unknown. As fuzzy uncertainty analyses for non-linear models and non-monotonic results require efficient optimization methods, a method based on evolutionary genetic algorithm has been used.
机译:开发水分配系统仿真模型中最重要的步骤之一就是提供仿真结果对输入值不确定性的依赖性。通过仿真模型传播不确定性的信息,为以有效和经济(低成本)的方式改进通用模型提供了基础。除了基于统计的不确定性和敏感性分析之外,模糊集理论还提供了一种替代方法,不需要输入参数分布的统计统计量。不确定性由模糊集参数表示,该参数与统计背景没有直接对应关系,尽管可以很容易地识别不确定性的迹象。在本文介绍的分析中,将适用于Becej社区的模型水分配系统中的旧管道的粗糙度作为不确定性参数,因为正确的值及其统计分布未知。由于非线性模型的模糊不确定性分析和非单调结果需要有效的优化方法,因此使用了基于进化遗传算法的方法。

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