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

Abstract:

Article Preview

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.

Info:

Periodical:

Key Engineering Materials (Volumes 474-476)

Edited by:

Garry Zhu

Pages:

436-441

DOI:

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

Citation:

J. W. Xu et al., "Reliability Analysis of Automotive Rear-Axle Bumper by Using Adaptive Neural-Fuzzy Inference System", Key Engineering Materials, Vols. 474-476, pp. 436-441, 2011

Online since:

April 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.