Reliability Analysis of Automotive Rear-Axle Bumper by Using Adaptive Neural-Fuzzy Inference System

被引：1

作者：

Xu, Jiawei ^{[1
]}

Park, Seop Hyeong ^{[1
]}

Fei, Xianyun ^{[2
]}

机构：

[1] Hallym Univ, Dept Elect Engn, Chunchon 200702, Gangwon Do, South Korea

[2] Huaihai Inst Technol, Lianyungan, Peoples R China

来源：

ADVANCED MATERIALS AND COMPUTER SCIENCE, PTS 1-3 | 2011年 / 474-476卷

关键词：

Adaptive Neural-fuzzy inference system(ANFIS); Membership function; Fuzzy logic(FL); Weibull Distribution;

D O I：

10.4028/www.scientific.net/KEM.474-476.436

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Adaptive neuro-fuzzy inference system[1] is an advanced algorithm to estimate important parameters based on limited available information. We conducted a specific analysis about this algorithm to validate our viewpoint compared with Weibull distribution[2], and rear-axle bumper was used for our experiment. The experimental results indicate that ANFIS can be more precise than Weibull distribution and more close to the real circumstances. According to the root mean square root that decreases to a relatively low value, we could infer that ANFIS is a good approach to estimate all data based on the limited given samples.

引用

页码：436 / +

页数：2