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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/18366

Title: An Expert System of Price Forecasting for Used Cars Using Adaptive Neuro-Fuzzy Inference
Authors: Wu, Jian-Da;Hsu, Chuang-Chin;Chen, Hui-Chu
Contributors: 車輛科技研究所
Keywords: Price forecasting;Artificial neural networks;Adaptive neuro-fuzzy inference system;Used car
Date: 2009-05
Issue Date: 2014-04-29T07:28:16Z
Publisher: Elsevier Ltd
Abstract: An expert system for used cars price forecasting using adaptive neuro-fuzzy inference system (ANFIS) is presented in this paper. The proposed system consists of three parts: data acquisition system, price forecasting algorithm and performance analysis. The effective factors in the present system for price forecasting are simply assumed as the mark of the car, manufacturing year and engine style. Further, the equipment of the car is considered to raise the performance of price forecasting. In price forecasting, to verify the effect of the proposed ANFIS, a conventional artificial neural network (ANN) with back-propagation (BP) network is compared with proposed ANFIS for price forecast because of its adaptive learning capability. The ANFIS includes both fuzzy logic qualitative approximation and the adaptive neural network capability. The experimental result pointed out that the proposed expert system using ANFIS has more possibilities in used car price forecasting.
Relation: Expert Systems with Applications, 36(4): 7809-7817
Appears in Collections:[車輛科技研究所] 期刊論文

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