Characteristics forecasting of hydraulic valve based on grey correlation and ANFIS

被引:18
作者
Jia, Zhen-Yuan [1 ]
Ma, Jian-Wei [1 ]
Wang, Fu-Ji [1 ]
Liu, Wei [1 ]
机构
[1] Dalian Univ Technol, Minist Educ, Key Lab Precis & Nontradit Machining Technol, Dalian 116024, Peoples R China
关键词
Forecasting; Grey correlation analysis; Adaptive neuro-fuzzy system; Hydraulic valve; COMPONENT ANALYSIS; NEURAL-NETWORK; FUZZY; SYSTEM;
D O I
10.1016/j.eswa.2009.06.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Accurate prediction is crucial for the synthesis characteristics of the hydraulic valve in industrial production. A prediction method (G-ANFIS for short) based on grey correlation and adaptive neuro-fuzzy system (ANFIS) to forecast synthesis characteristics of hydraulic valve is devised and the utilizing of the method can help enterprises to decrease the repair rate and reject rate of the product. Grey correlation model is used first to get the main geometric elements affecting the synthesis characteristics of the hydraulic valve and thus simplifies the system forecasting model. Then use ANFIS to build a prediction model based on the above mentioned main geometric elements To illustrate the applicability and capability of the devised prediction method, a specific hydraulic valve production was used as a case study. The results demonstrate that the prediction method was applied successfully and could provide high accuracy. The method performed better than artificial neural networks (ANN) to forecast the synthesis characteristics of hydraulic valve. (C) 2009 Elsevier Ltd All rights reserved.
引用
收藏
页码:1250 / 1255
页数:6
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