Title :
The application of dynamic intelligent neural network in time series forecasting
Author :
Huang, Mengtao ; Zhang, Ruimin
Author_Institution :
Dept. of Electr. Control & Eng., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
Abstract :
The research of artificial neuron network has been maturated both in theory and practical application, so it is also employed into nonlinear time series forecasting. However, concerning with the problem of time series forecasting based on traditional neural network, such as black box, poor accuracy, and facing the shortage of post knowledge, the dynamic intelligent neural network is proposed in the paper, a different neural network forecasting model built up by dynamic prediction and intelligent neuron, which improves the predictive performance with a high accuracy. Finally, the paper takes the prediction of the time series of MinCurrent, a industrial parameter in the oil work, for example to illustrate the feasibility and efficiency of the technique.
Keywords :
forecasting theory; neural nets; time series; artificial neuron network; dynamic intelligent neural network application; industrial parameter; nonlinear time series forecasting; Artificial neural networks; Biological neural networks; Cognition; Forecasting; Neurons; Predictive models; Time series analysis; dynamic prediction model; intelligent neuron; neural network; time series;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
DOI :
10.1109/ICECENG.2011.6057422