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An Integrated Fuzzy Simulation-Optimization Model for Supporting Low Impact Development Design under Uncertainty

机译:不确定性下支持低冲击开发设计的集成模糊仿真优化模型

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摘要

Seeking cost-effective design of urban hydrological facilities and drainage systems is an important task for many city planners. However, such a process has always been complicated with intrinsic uncertainties. This work presented an integrated fuzzy simulation-optimization model (FSOM) for supporting Low Impact Development (LID) design under model uncertainties. Various LID implementation schemes involving green roof, bio-retention cell, and permeable pavement were simulated through an urban hydrological model. Three model parameters were assumed as fuzzy sets. In a case study, fuzzy simulation (FS) and genetic algorithm (GA) were employed to search the optimal schemes of LIDs under various confidence levels of satisfying flood control constraints. Comparison of FSOM to traditional deterministic and stochastic models were also carried out. It was shown that FSOM could offer a flexible way of defining and assessing uncertainties associated with hydrological modeling and generate solutions that were comparable to those from either deterministic or stochastic models. However, FSOM also showed limitation of high computational requirement.
机译:寻求具有成本效益的城市水文设施和排水系统设计是许多城市规划者的重要任务。但是,这样的过程一直很复杂,存在固有的不确定性。这项工作提出了一个集成的模糊仿真优化模型(FSOM),用于支持模型不确定性下的低影响开发(LID)设计。通过城市水文模型模拟了各种LID实施方案,包括屋顶绿化,生物保留单元和渗透性路面。假定三个模型参数为模糊集。在一个案例研究中,采用模糊仿真(FS)和遗传算法(GA)来搜索满足洪水控制约束的各种置信度下的LID的最优方案。还将FSOM与传统的确定性和随机模型进行了比较。结果表明,FSOM可以提供一种灵活的方法来定义和评估与水文模型相关的不确定性,并生成与确定性或随机模型可比的解决方案。但是,FSOM也显示出高计算要求的局限性。

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