Title :
Research on Forecast Model for Sustainable Development of Economy-Environment System Based on PCA and SVM
Author :
Li, Yan ; Wu, You-xi ; Zeng, Zhen-Xiang ; Guo, Lei
Author_Institution :
Sch. of Manage., Hebei Univ. of Technol., Tianjin
Abstract :
According to the complexity of economy-environment system and many environmental indicators, which influence the development of economy, we first use principal component analysis (PCA) to realize the dimension reduction of the environmental indicators. Then a non-linear method - support vector regression (SVR), which is a part of support vector machine (SVM) is used to establish the forecast model for sustainable development of economy-environment system based on the data which are treated by PCA. Finally experiments based on the environmental indicators and gross domestic product (GDP) of Hebei province is given. The research shows that compared with neural network, SVR has simple mathematical model and high forecast precision
Keywords :
economic indicators; forecasting theory; principal component analysis; regression analysis; support vector machines; sustainable development; GDP; Hebei province; PCA; SVM; dimension reduction; economy-environment system; environmental indicator; forecast model; gross domestic product; neural network; nonlinear method; principal component analysis; support vector regression; sustainable development; Covariance matrix; Cybernetics; Economic forecasting; Economic indicators; Eigenvalues and eigenfunctions; Machine learning; Neural networks; Predictive models; Principal component analysis; Support vector machines; Sustainable development; Economy-Environment system; Gross Domestic Product; Principal Component Analysis; Support Vector Machine;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258576
