正弦余弦算法-投影寻踪水污染物总量分配模型

基于水资源禀赋条件、效率原则和尊重现状的原则,构建水污染物总量分配指标体系和水污染物分配投影寻踪(PP)模型。针对PP模型最佳投影方向难以确定的不足,利用正弦余弦算法(SCA)搜寻PP模型最佳投影方向,构建SCA-PP模型对云南省文山州壮族苗族自治州8县(市)水污染物控制总量进行分配。并通过6个典型测试函数对SCA算法进行仿真验证,仿真结果与蚁群优化(ACO)算法、模拟退火算法(SA)、文化算法(CA)、布谷鸟搜索(CS)算法和人工蜂群(ABC)算法进行对比。结果表明:(1)SCA算法寻优效果明显优于ACO、SA、CA、CS和ABC算法,具有模型简单、调节参数少、收敛速度快、寻优精度高、全局寻优能力强以及收敛稳定性与收敛可靠性好等特点。(2)SCA-PP模型水污染物控制总量分配结果符合区域经济社会发展和水污物染削减客观要求。模型及方法具有一定的可操作性和有效性,可为水污染物分配提供新的途径和方法。

Sine cosine algorithm-projection pursuit model for water pollutant load allocation

Based on the conditions of water resources endowment, the efficiency principle, and the principle of respecting actual conditions, an index system for water pollutant load allocation and a water pollutant allocation projection pursuit(PP)model were established. It is difficult to determine the optimal projection direction using the PP model. In order to solve this problem, the sine cosine algorithm(SCA)was used to search for the optimal projection direction of the PP model. An SCA-PP model was built for the water pollutant load allocation for eight counties(cities)in Wenshan Zhuang and Miao Autonomous Prefecture of Yunnan Province. The SCA algorithm was verified using six typical test functions. The simulation results were compared with those of the ant colony optimization(ACO)algorithm, simulated annealing(SA)algorithm, cultural algorithm(CA), Cuckoo search(CS)algorithm, and artificial bee colony(ABC)algorithm. The results are as follows: (1)The SCA algorithm performs better than the ACO, SA, CA, CS, and ABC algorithms. It is simple and has a fast convergence speed, high precision of optimization, high capability of global optimization, and strong convergence stability and reliability. (2)The simulations results of the SCA-PP model for water pollutant load control meet the economic and social development and water pollutant reduction requirements in the study area. The model has certain operability and effectiveness, providing a new method of water pollutant allocation.