Title :
Forecast Method of Steel Output based on Self-Adaptive Wavelet Neural Network Model
Author :
Lanjuan, Liu ; Qingchen, Shang ; Meiping, Xie
Author_Institution :
Sch. of Inf. Manage. & Eng., Shanghai Univ. of Finance & Econ.
Abstract :
Steel industry is one of the pillar industries in Chinese national economy, and has made an active contribution to the national economy´s sustained development. Therefore the study in prediction of steel output has become a very important task. In this paper, on the basis of reviewing the existing common prediction methods, we combine wavelet with neural network, put forward a data mining method based on self-adaptive wavelet neural network, and build a machine learning mechanism of data mining process to improve the capability of problem dealing. The demonstration results indicate that compared with general artificial neural network, data mining with self-adaptive wavelet neural network is not only effective but also feasible
Keywords :
data mining; learning (artificial intelligence); neural nets; self-adjusting systems; steel industry; data mining; forecast method; machine learning mechanism; prediction methods; self-adaptive wavelet neural network model; steel output; Artificial neural networks; Data mining; Iron; Metals industry; Neural networks; Ores; Prediction methods; Predictive models; Production; Steel; prediction study; self-adaptive wavelet neural network; steel output;
Conference_Titel :
Intelligent Systems, 2006 3rd International IEEE Conference on
Conference_Location :
London
Print_ISBN :
1-4244-01996-8
Electronic_ISBN :
1-4244-01996-8
DOI :
10.1109/IS.2006.348529