COMPARISION OF THE MULTIPLE REGRESSION, ANN, AND ANFIS MODELS FOR PREDICTION OF MOE VALUE OF OSB PANELS

被引：0

作者：

Yapici, Fatih ^{[1
]}

Senyer, Nurettin ^{[2
]}

Esen, Rasit ^{[3
]}

机构：

[1] Ondokuz Mayis Univ, Fac Engn, Dept Ind Engn, TR-55139 Samsun, Turkey

[2] Ondokuz Mayis Univ, Fac Engn, Dept Comp Engn, TR-55139 Samsun, Turkey

[3] Karabuk Univ, Fine Art Fac, Dept Ind Prod Design, TR-78050 Karabuk, Turkey

来源：

WOOD RESEARCH | 2016年 / 61卷 / 05期

关键词：

OSB; multiple regression; ANN; ANFIS; mechanical properties; NEURAL-NETWORKS;

D O I：

暂无

中图分类号：

TB3 [工程材料学]; TS [轻工业、手工业、生活服务业];

学科分类号：

0805 ; 080502 ; 0822 ;

摘要：

This research investigates the prediction of modulus of elasticity (MOE) properties, which is the most important properties in many applications, of the oriented strand board (OSB) produced under different conditions (pressing time, pressing pressure, pressing temperature and adhesive ratios) by multiple regression, artificial neural network (ANN) and adaptive Neurofuzzy inference system (ANFIS). Software computing techniques are now being used instead of statistical methods. It was found that the constructed ANFIS exhibited a higher performance than multiple regression and ANN for predicting MOE.Software computing techniques are very useful for precision industrial applications and, also determining which method gives the highest accurate result.

引用

页码：741 / 754

页数：14

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