基于改进人工鱼群算法的三江平原投影寻踪旱情评价模型

Projection pursuit model for evaluating drought based on improved artificial fish swarm algorithm of Sanjiang Plain

针对现有的旱情评价方法容易出现评价等级离散和结果不易分辨等问题,提出了基于人工鱼群的投影寻踪旱情评价模型,利用人工鱼群算法优化投影指标函数寻求最佳投影方向,同时采用自适应人工鱼步长和拥挤度因子对人工鱼群算法进行改进,克服其易陷入局部最优等缺点,提高了全局搜索能力和收敛速度。以三江平原红兴隆分局为例,选用降雨距平百分率、Z指标和降水温度均一化指标3个指标综合计算投影值,建立了基于改进人工鱼群算法的三江平原投影寻踪旱情评价模型。结果表明,该模型有效避免了单项指标评价的不相容性,用于区域旱情评价是切实可行的,为旱情评价提供了参考。

Projection pursuit model for comprehensive evaluation of drought was established by using artificial fish swarm. It was superior to the existing methods which might cause many problems such as discrete evaluation grade and barely recognizable results. Artificial fish swarm algorithm （AF） was introduced to optimize the function and seek the optimum projection vector,and it was improved by using the adaptive artificial fish step and crowded degree factor. Compared to the previous methods,it overcame the shortcomings which were easily to fall into local extreme optimum and improved the global search ability and convergence speed. Taking Hongxinglong Branch Bureau of Sanjiang Plain as the research objects,the departure ratio of rain-fall,Z index and homogenization of rain-temperature were selected to establish drought assessment model based on above methods. The results showed that the model could avoid the incompatibility of single indexes. The improved projection pursuit method is feasible to evaluate the drought.