A fuzzy case-based reasoning model for sales forecasting in print circuit board industries

被引：71

作者：

Chang, Pei-Chann ^{[1
,2
]}

Liu, Chen-Hao ^{[2
]}

Lai, Robert K. ^{[3
]}

机构：

[1] Yuan Ze Univ, Dept Informat Managemnet, Chungli 32026, Taiwan

[2] Yuan Ze Univ, Dept Ind Engn & Management, Chungli 32026, Taiwan

[3] Yuan Ze Univ, Dept Comp Sci & Engn, Chungli 32026, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2008年 / 34卷 / 03期

关键词：

fuzzy multi-criteria decision making; case-based reasoning; sales forecasting; printed circuit boards;

D O I：

10.1016/j.eswa.2007.02.011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Reliable prediction of sales can improve the quality of business strategy. Case-based reasoning (CBR), one of the well known artificial intelligence (AI) techniques, has already proven its effectiveness in numerous studies. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures in CBR, it is very difficult to find the similar cases from case bases. In order to deal with this problem, fuzzy theories have been incorporated into CBR allowing for more flexible and accurate models. This research develops a fuzzy case-based reasoning (FCBR) and explores its potential use in supporting a forecaster during the forecast process for forecasting the future sales of a printed circuit board factory. Numerical data of various affecting factors and actual demand of the past 5 years of the printed circuit board (PCB) factory are collected and input into the FCBR for future monthly sales forecasting. Experimental results show the effectiveness of the FCBR model when comparing it with other approaches. (c) 2007 Elsevier Ltd. All rights reserved.

引用

页码：2049 / 2058

页数：10

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