PSO_ACO聚类分析在中国区域经济协调发展评价中的应用

Regional Economy Coordination Development Evaluation in China Based on PSO and ACO Cluster Analysis

结合粒子群算法(PSO)、蚁群算法(ACO),对中国31个地区的经济协调发展水平进行聚类分析。首先构建区域经济协调发展水平评价指标体系,并借助主成分分析对样本数据做降维处理;然后利用PSO生成ACO所需的初始信息素,对中国2014年的区域经济协调发展水平做聚类分析。仿真表明,PSO_ACO聚类分析结果与客观实际吻合度较高。

The particle swarm optimization algorithm （PSO） and ant colony algorithm （ACO） are used to analyze the coordinated development level of 31 regions in China. Firstly, the evaluation index system of coordinated development level of regional economy is constructed, and the principal component analysis is used to reduce the dimension of sample data. Then PSO is used to generate the initial pheromone of ACO, cluster analysis on the coordinated development level of regional economy in China in 2014. The simulation test proves that the evaluation results conform to the objective situation by this means.