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Genetic Algorithm Based Combinational Evaluation Model for Regional Water Security Evaluation; a Case Study

机译:基于遗传算法的区域水安全综合评价模型案例研究

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Water Security crisis is one of the most cut-throat challenges to sustainable socio economic development in the world. In this paper, considering the pros and cons of both the subjective and objective weighting evaluation methods, a new Combinational Evaluation Model based on Genetic Algorithm (CEM-GA), integrating four single evaluation methods with the Minimizing Difference Degree Model based on Nash Equilibrium in Game Theory and Genetic Algorithm as the coordinated objective, was developed for regional water security evaluation. The case study of North River basin in Guangdong province in China illustrated the methodology. The results suggests that CEM-GA combines information on both subjective and objective weights, hence objective evaluation information and the requirements of the decision-maker can be well balanced. As a practical method, it can be widely used for the quantitative evaluation and comparison of water security states in different regions.
机译:水安全危机是世界可持续社会经济发展面临的最严峻挑战之一。本文考虑了主观和客观加权评估方法的优缺点,提出了一种新的基于遗传算法的组合评估模型(CEM-GA),将四种单一评估方法与基于纳什均衡的最小化差异度模型相结合。开发了博弈论和遗传算法作为协调目标,用于区域水安全评价。以中国广东省北部流域为例,说明了该方法。结果表明,CEM-GA结合了主观和客观权重的信息,因此可以很好地平衡客观评估信息和决策者的要求。作为一种实用的方法,可广泛用于不同地区水安全状况的定量评估和比较。

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