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Groundwater management using a new coupled model of meshless local Petrov-Galerkin method and modified artificial bee colony algorithm

机译:使用新的无网格局部Petrov-Galerkin方法和改进的人工蜂群算法耦合模型进行地下水管理

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摘要

To develop sustainable groundwater management strategies, generally coupled simulation-optimization (SO) models are used. In this study, a new SO model is developed by coupling moving least squares (MLS)-based meshless local Petrov-Galerkin (MLPG) method and modified artificial bee colony (MABC) algorithm. The MLPG simulation model utilizes the advantages of meshless methods over the grid-based techniques such as finite difference (FDM) and finite element method (FEM). For optimization, the basic artificial bee colony algorithm is modified to balance the exploration and exploitation capacity of the model more effectively. The performance of the developed MLPG-MABC model is investigated by applying it to hypothetical and field problems with three different management scenarios. The model results are compared with other available SO model solutions for its accuracy. Further, sensitivity analyses of various model parameters are carried out to check the robustness of the SO model. The proposed model gave quite promising results, showing the applicability of the present approach.
机译:为了制定可持续的地下水管理策略,通常使用耦合的模拟优化(SO)模型。在这项研究中,通过耦合基于移动最小二乘(MLS)的无网格局部Petrov-Galerkin(MLPG)方法和改进的人工蜂群(MABC)算法,开发了一个新的SO模型。 MLPG仿真模型利用了无网格方法相对于基于网格的技术(如有限差分(FDM)和有限元方法(FEM))的优势。为了优化,对基本的人工蜂群算法进行了修改,以更有效地平衡模型的探索和开发能力。通过将其应用于具有三种不同管理方案的假设和现场问题,研究了开发的MLPG-MABC模型的性能。将模型结果与其他可用的SO模型解决方案的准确性进行比较。此外,对各种模型参数进行敏感性分析以检查SO模型的鲁棒性。所提出的模型给出了非常有希望的结果,表明了本方法的适用性。

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