Time series forecasting through rule-based models obtained via rough sets

被引：4

作者：

Faustino, Claudio Paulo ^{[1
]}

Pinheiro, Carlos Alberto M. ^{[1
]}

Carpinteiro, Otavio A. ^{[1
]}

Lima, Isaias ^{[1
]}

机构：

[1] Fed Univ Itabuba, Res Grp Syst & Comp Engn, BR-37500903 Itajuba, MG, Brazil

来源：

ARTIFICIAL INTELLIGENCE REVIEW | 2011年 / 36卷 / 04期

关键词：

Forecasting; Time series; Rough sets; Rule-based models;

D O I：

10.1007/s10462-011-9215-0

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Prediction models based on artificial intelligence techniques have been widely used in Time Series Forecasting in several areas. They are often fuzzy models or neural networks. However, the use of rough sets based models have not yet been explored. The aim of this work is to introduce a new approach which uses rough set concepts to obtain rule-based models capable to perform time series forecasting.

引用

页码：299 / 310

页数：12

共 21 条

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