Application of community detection based on improved genetic algorithm in air pollutant propagation network

Abstract

In order to analyze the propagation relationship of air pollutants in the Beijing-Tianjin-Hebei region, this paper applies the complex network to the air pollutant propagation model by analyzing the airborne pollutant propagation characteristics. A new community detection algorithm based on genetic algorithm is proposed to analyze the characteristics of air pollutant propagation network. The algorithm has combined the advantages of label propagation algorithm. The concept of community structure is added to the crossover operator, and the constrained mutation operator is used to carry out the mutation operation, so as to achieve the evolution of the population. The algorithm has found out that the air pollutant propagation network does have a community structure.