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Indexed by : Article

Document Code : 000423369800021

First Author : 熊峰

Author : 马正东,Shuming Chen,吕天同,刘芳

Date of Publication : 2018-02-01

Journal : STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

Included Journals : SCI  

Affiliation of Author(s) : Jilin Univ

Place of Publication : NY 10013 USA

Discipline : 工学

Funded by : national key research and development project；State Scholarship Fund of China Scholarship Council

Document Type : J

Volume : 57

Issue : 2

Page Number : 829-847

ISSN : 1615-147X

Key Words : Contribution analysis method; RBFNN-RSM; MOPSO; TOPSIS; Multi-objective lightweight design

Teaching and Research Group : State Key Lab Automot Simulat & Control

Abstract : This paper proposes a hybrid method combining the Contribution Analysis Method, the Radial Basis Function Neutral Network (RBFNN)-Response Surface Method (RSM) hybrid surrogate modeling method, the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), used for structure-material integrated multi-objective lightweight design of the front end structure of an automobile body. First, Contribution Analysis Method provides an effective approach to determine the final parts for lightweight design, and fourteen th

First-Level Discipline : 机械工程

Translation or Not : no