Intelligent Cockpit Perceptual Image Prediction Based on BP Neural Network Optimization Genetic Algorithm

被引：0

作者：

Chen G. ^{[1
]}

Shen Z. ^{[1
]}

Sun L. ^{[2
]}

Zhi M. ^{[2
]}

Li T. ^{[2
]}

机构：

[1] School of Mechanical Engineering, Yanshan University, Qinhuangdao

[2] School of Art and Design, Yanshan University, Qinhuangdao

来源：

Qiche Gongcheng/Automotive Engineering | 2023年 / 45卷 / 08期

关键词：

BP neural network; genetic algorithm; intelligent cockpit modeling optimization; perceptual image prediction;

D O I：

10.19562/j.chinasae.qcgc.2023.08.018

中图分类号：

学科分类号：

摘要：

In order to reduce subjective interference and meet the diverse emotional needs of users，the design method of intelligent cockpit perceptual image prediction based on BP neural network optimization genetic algorithm is proposed. From the user's point of view，user emotional image is obtained and the intensity is divided. Factor analysis method is used to reduce dimension to obtain target images and cockpit samples of new energy vehicles. Cluster analysis method is applied to screen and obtain advantage samples and the modeling characteristic factors of intelligent cockpit central control are extracted by combining with morphological analysis method. Based on BP neural network，the mapping model of specific target image and modeling feature factors is constructed，and the functional relationship between the two is obtained，which is used as fitness function to carry out genetic algorithm analysis，optimize the optimal combination of modeling factors under the specific image，and complete the combination of evaluation method and optimization method. According to the combination of advantage factors，the design practice is carried out to verify the practicability of the method. The results show that the method can effectively meet the multidimensional emotional needs of users，and provide a new idea and reference for the diversification of intelligent cockpit modeling design. © 2023 SAE-China. All rights reserved.

引用

页码：1479 / 1488

页数：9

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