Cost estimation using ANFIS

被引：10
|
作者：
Lotfi, Ehsan [1 ]
Darini, M. [2 ]
Karimi-T, M. R. [3 ]
机构：
[1] Islamic Azad Univ, Torbat E Jam Branch, Dept Comp Engn, Torbat E Jam, Iran
[2] Islamic Azad Univ, Torbat E Jam Branch, Dept Management, Torbat E Jam, Iran
[3] Islamic Azad Univ, Torbat E Jam Branch, Dept Accounting, Torbat E Jam, Iran
来源：
ENGINEERING ECONOMIST | 2016年 / 61卷 / 02期
关键词：
ARTIFICIAL NEURAL-NETWORKS; FUZZY INFERENCE SYSTEM; DEMAND; ELECTRICITY; PRICE; OIL;
D O I：
10.1080/0013791X.2015.1104568
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Cost function estimation is vital for decision-making in project management. In this article, a novel cost estimator is investigated based on an adaptive neuro-fuzzy inference system(ANFIS). In the numerical studies, ANFIS is tested to modeling pressure vessel cost as a case study. According to the comparative results, ANFIS shows better accuracy than multiple linear regression (MLR), Taylor Kriging (TK), and artificial neural networks (ANNs). Hence, ANFIS can be applicable to various cost function estimation problems.
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页码：144 / 154
页数：11
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