Title :
Energy Output Prediction Model on Time Series Analysis and Neural Network
Author :
Feng Shu-hu ; Guan Xiao-ji
Author_Institution :
China Univ. of Min. & Technol., Beijing
Abstract :
There are a large number of time series problems. In order to research structure and law of system we need to structure time series model which is used to predict and analysis this system. Now time series analysis methods adopt usually AR (Autoregressive) or ARMA (Autoregressive-Moving Average) model, but the actual problems are too complex to attain result and apply to in practice. At first this article analyzes the basis principle of production system time series and sets up time series-artificial neural network model by BP neural network, then predicts energy output by this model. This model has advantages of convenience, excellent dynamic capability, high prediction veracity, etc., which has practical value in reality.
Keywords :
autoregressive moving average processes; mathematics computing; neural nets; artificial neural network; autoregressive-moving average; energy output prediction model; time series analysis; Artificial neural networks; Damping; Differential equations; Fluctuations; Mathematical model; Neural networks; Predictive models; Production systems; System identification; Time series analysis;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1311-9
DOI :
10.1109/WICOM.2007.1230