The Fuzzy-AI Modeling for Optimization of Long-Term Metro Vehicle Repair

Author

Shaopei, Lin ; Hong, Zheng ; Hao, Hu ; Jun, Yan

Author_Institution

Shanghai Jiao Tong Univ., Shanghai, China

Volume

6

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

459

Lastpage

463

Abstract

In this paper, the Â¿fuzzy-AI modelÂ¿ is applied for investment decision of optimum repair of multiple metro vehicles. The model solves this highly uncertain and sophisticated problem both based on its fuzzy analysis and reasoning of existing distressed metro vehicles. The VDSI (vehicle distress state indicator) is used in finding the optimum investment management of repair, which is a fuzzy synthesis of quantized indicator for the distressed vehicle. An optimization of long-term vehicle repair investment planning is suggested.

Keywords

fuzzy set theory; maintenance engineering; optimisation; planning; road vehicles; fuzzy analysis; fuzzy synthesis; fuzzy-AI modeling; long-term metro vehicle repair; long-term vehicle repair investment planning; optimum investment management; vehicle distress state indicator; Appraisal; Cost function; Employee welfare; Fuzzy reasoning; Fuzzy systems; Humans; Investments; Rail transportation; Telecommunication traffic; Vehicles; Fuzzy-AI model; investment decision; metro vehicle repair; vehicle distress state indicator;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3735-1

Type

conf

DOI

10.1109/FSKD.2009.756

Filename

5359894