鸡群优化算法-投影寻踪洪旱灾害评估模型

Projection pursuit model for evaluation of flood and drought disasters based on chicken swarm optimization algorithm

利用15个复杂函数对鸡群优化算法进行仿真验证,并同狼群算法、粒子群算法、鱼群算法和遗传算法进行对比。利用鸡群优化算法搜寻投影寻踪模型最佳投影方向,建立鸡群优化算法-投影寻踪洪旱灾害评估模型。以文山州1990—2013年洪旱灾害评估为例,分别选取受灾人口等5个洪灾评估指标及农作物受灾面积等4个旱灾评估指标,利用洪旱灾害投影系列均值及标准差构造洪旱灾害评估分级标准对实例进行评估。结果表明:鸡群优化算法具有较好的计算鲁棒性和全局寻优能力。将该算法用于投影寻踪模型最佳投影方向的选取,可有效提高评估精度,避免最佳投影方向寻优结果变化范围过大的缺陷。

The chicken swarm optimization algorithm was validated using 15 complex functions, and the simulated results were compared with those of the Wolf algorithm, particle swarm optimization algorithm, fish swarm algorithm, and genetic algorithm. Using the chicken swarm optimization to search for the optimal projection direction of the projection pursuit model, a projection pursuit evaluation model was established. Using assessment of flood and drought disasters from 1990 to 2013 in Wenshan Prefecture as an example, five flood disaster evaluation indices, including disaster-affected population, and four drought disaster evaluation indices, including the disaster area of crops, were selected, and grading standards for flood and drought disaster assessment were constructed with the mean and standard deviation of the flood and drought disaster projection series. The results show that the chicken swarm optimization algorithm is robust and has high global optimization ability. Using the algorithm to select the optimal projection direction of the projection pursuit model can effectively improve the evaluation accuracy and prevent a high degree of variation from occurring in the optimal projection direction.