An expert system of price forecasting for used cars using adaptive neuro-fuzzy inference

被引:54
|
作者
Wu, Jian-Da [1 ]
Hsu, Chuang-Chin [1 ]
Chen, Hui-Chu [2 ]
机构
[1] Natl Changhua Univ Educ, Grad Inst Vehicle Engn, Changhua 500, Changhua, Taiwan
[2] Natl Changhua Univ Educ, Dept Ind Educ & Technol, Changhua 500, Changhua, Taiwan
关键词
Price forecasting; Artificial neural networks; Adaptive neuro-fuzzy inference system; Used car; REGIONAL ELECTRICITY LOADS; SHORT-TERM; NETWORKS; PREDICTION;
D O I
10.1016/j.eswa.2008.11.019
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7809 / 7817
页数:9
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