Hybrid Method for Forecasting Next Values of Time Series for Intelligent Building Control

被引：2
|
作者：
Stachno, Andrzej [1 ]
Jablonski, Andrzej [1 ]
机构：
[1] Wroclaw Univ Technol, Fac Elect, PL-50370 Wroclaw, Poland
来源：
COMPUTER AIDED SYSTEMS THEORY - EUROCAST 2015 | 2015年 / 9520卷
关键词：
Artificial neuron networks; FFT; Forecasting; Successive values of a time series; Moving Window Fourier; Environmental measurements in an intelligent building;
D O I：
10.1007/978-3-319-27340-2_101
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The method for forecasting successive values of time series with the application of Artificial Neural Networks and Moving Window Fourier takes into account additional parameters. Such parameters are determined by an external observer based on an analysis of the accuracy of forecasts obtained. For the purpose of automating the above method, a parameter selection module based on decision trees has been proposed. In this way the Hybrid Method for Forecasting (HMF) successive values of time series has been created.
引用
收藏
页码：822 / 829
页数：8
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