Path optimization of open collaborative innovation of energy industry in urban agglomeration based on particle swarm optimization algorithm

Abstract

To study the open collaborative innovation path optimization of urban agglomeration energy industry based on particle swarm optimization algorithm. Firstly, this paper brings industrial agglomeration and urban agglomeration into a unified analytical framework, uses location entropy and spatial Gini coefficient to measure the degree of industrial agglomeration, and evaluates the degree of regional industrial agglomeration competitiveness by constructing an evaluation index system of industrial agglomeration competitiveness. Then, the agglomeration index system was established, the development degree analysis method and Carlino model were used to analyze the development degree and agglomeration degree of eco-economic zones, and the agglomeration effect was analyzed by dynamic econometric method and spatial autocorrelation statistical method. Finally, a regional collaborative innovation capability evaluation model based on particle swarm optimization algorithm is constructed. Based on the index system and evaluation model, this paper evaluates and analyzes the collaborative innovation capability, and puts forward countermeasures and suggestions for future collaborative development.

Keywords

• Particle swarm optimization
• Urban agglomeration
• Energy industry
• Collaborative innovation
• Path optimization