Title :
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
Abstract :
In this paper, the ¿fuzzy-AI model¿ 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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.756
