The influence of input data standardization method on prediction accuracy of artificial neural networks

被引：64

作者：

Anysz, Hubert ^{[1
]}

Zbiciak, Artur ^{[1
]}

Ibadov, Nabi ^{[1
]}

机构：

[1] Warsaw Univ Technol, Fac Civil Engn, Armii Ludowej16, PL-00637 Warsaw, Poland

来源：

XXV POLISH - RUSSIAN - SLOVAK SEMINAR -THEORETICAL FOUNDATION OF CIVIL ENGINEERING | 2016年 / 153卷

关键词：

input data standardization; artificial neural networks ANN; building contracts completion date predicting;

D O I：

10.1016/j.proeng.2016.08.081

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Achieving good results in applying artificial neural networks (ANN) in predicting requires some preparatory works on the set of data. One of them is standardization which is necessary when nonlinear activation function is applied. Basing on predicting completion period of building contracts by multi-layer ANN with error backpropagation algorithm, six different methods of input data standardization were checked in order to determine which allows to achieve the most accurate predictions. (C) 2016 The Authors. Published by Elsevier Ltd.

引用

页码：66 / 70

页数：5

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