The prediction of the electric field level in the reverberation chamber depending on position of stirrer

被引：5

作者：

Nisanci, M. H. ^{[2
]}

Kucuksille, E. U. ^{[3
]}

Cengiz, Y. ^{[1
]}

Orlandi, A. ^{[2
]}

Duffy, A. ^{[4
]}

机构：

[1] Suleyman Demirel Univ, Dept Elect & Commun Engn, TR-32260 Isparta, Turkey

[2] Univ Laquila, Dept Elect Engn, I-67100 Laquila, Italy

[3] Suleyman Demirel Univ, Dept Comp Engn, TR-32260 Isparta, Turkey

[4] De Montfort Univ, Dept Elect Engn, Leicester LE1 9BH, Leics, England

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 03期

关键词：

Electric field; Reverberation chamber; Data mining;

D O I：

10.1016/j.eswa.2010.07.093

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This study presents nine modeling techniques within data mining process for the prediction of electric field level which depends on the positions of stirrer in the mode stirred reverberation chamber. These are Linear Regression (LR), Multi Layer Perceptron (MLP), Pace Regression (PR), KStar, Regression by discretization (RD), Random SubSpace (RS), M5P, RepTree and Decision Table models. Relations depending on frequency and position of stirrer have been carried out for the determination of electric field in the reverberation chamber. Obtained model results for each stirrer steps have been compared and the best model has been investigated. Results indicate that the use of derived formulation from these techniques will facilitate design and optimize of location of maxima (mode) and minima (null) of electric field in the reverberation chamber which a component of especially mode stirrer reverberation chamber test method. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：1689 / 1696

页数：8

共 31 条

[1] Assessment of diffuse solar energy under general sky condition using artificial neural network [J].