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Indexed by:期刊论文

Date of Publication:2011-07-01

Journal:EXPERT SYSTEMS WITH APPLICATIONS

Included Journals:SCIE、EI

Volume:38

Issue:7

Page Number:8030-8036

ISSN No.:0957-4174

Key Words:Characteristics prediction; Simulated annealing; SVM; Hydraulic valve

Abstract:Accurate prediction for the synthesis characteristics of hydraulic valve in industrial production plays an important role in decreasing the repair rate and the reject rate of the product. Recently, Support Vector Machine (SVM) as a highly effective mean of system modeling has been widely used for predicting. However, the important problem is how to choose the reasonable input parameters for SVM. In this paper, a hybrid prediction method (SA-SVM for short) is proposed by using simulated annealing (SA) and SVM to predict synthesis characteristics of the hydraulic valve, where SA is used to optimize the input parameters of SVM based prediction model. To validate the proposed prediction method, a specific hydraulic valve production is selected as a case study. The prediction results show that the proposed prediction method is applicable to forecast the synthesis characteristics of hydraulic valve and with higher accuracy. Comparing with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANN) are also made. (C) 2010 Elsevier Ltd. All rights reserved.