Improved Particle Swarm Optimization for Selection of Shield Tunneling Parameter Values

• 作者: Cong Jin Gongyu Hou Xin Liu Zhedong Xu
• 来源期刊: 工程与科学中的计算机建模(英文)
• 学科: 工学
• 关键词: INERTIA WEIGHT EAIW-IPSO SELF-REGULATION mechanism SHIELD TUNNELING parameter.
• 年，卷（期）: 2019,（2）
• 页码范围: 317-337
• 页数: 21页
• 分类号: TP1

摘要

This article proposes an exponential adjustment inertia weight immune particle swarm optimization(EAIW-IPSO)to enhance the accuracy and reliability regarding the selection of shield tunneling parameter values.According to the iteration changes and the range of inertia weight in particle swarm optimization algorithm(PSO),the inertia weight is adjusted by the form of exponential function.Meanwhile,the self-regulation mechanism of the immune system is combined with the PSO.12 benchmark functions and the realistic cases of shield tunneling parameter value selection are utilized to demonstrate the feasibility and accuracy of the proposed EAIW-IPSO algorithm.Comparison with other improved PSO indicates that EAIW-IPSO has better performance to solve unimodal and multimodal optimization problems.When solving the selection of shield tunneling parameter values,EAIW-IPSO can provide more accurate and reliable references for the realistic engineering.