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Model of projection pursuit drought evaluation based on improved artificial fish swarm algorithm of Sanjiang Plain

机译:基于改进型人工鱼群算法的投影寻踪干旱评估模型

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The model of projection pursuit drought evaluation based on artificial fish swarm algorithm was proposed to optimize the function and seek the optimum projection for solving the problems such as discrete evaluation grade and low resolved results obtained by using other methods. In order to avoid local optimization and improve global search ability and convergence speed of the algorithm, the adaptive artificial fish step and crowded degree factor were applied to optimize artificial fish swarm algorithm. The departure ratio of rain-fall, Z index and homogenization of rain-temperature were selected to establish evaluation model of Sanjiang Plain based on above methods. The results showed that model effectively avoided the incompatibility of single index. It was feasible to evaluate actual drought situation, and provide a new way for drought evaluation.
机译:提出了一种基于人工鱼群算法的投影寻踪干旱评价模型,以优化该函数,寻求最优投影,以解决离散评价等级,其他方法求解结果差等问题。为了避免局部优化,提高算法的全局搜索能力和收敛速度,采用自适应人工鱼阶和拥挤度因子对人工鱼群算法进行优化。在上述方法的基础上,选择了降雨的离差率,Z指数和雨水均匀度,建立了三江平原评价模型。结果表明,该模型有效地避免了单一指标的不兼容。评价干旱的实际情况是可行的,并为干旱评价提供了新的途径。

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