Title :
Forecast of Regional Gross National Product Based on Grey Modelling Optimized by Genetic Algorithm
Author :
Xie, Qi ; Xie, Yan
Author_Institution :
Sch. of Law & Commence, Wuhan Inst. of Technol., Wuhan, China
Abstract :
Regional gross national product (GDP) is an important indicator of national economic accounting. Regional GDP is an important part of the country´s GDP, and it is of great significance for formulating scientifically the strategy and the policy of regional development that to effectively forecast regional GDP. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey forecast model and characteristics of genetic algorithm to find global optimization. So the forecast model is more accurate. According to data from a province, the GM (1, 1) model for forecasting regional GDP was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as regional GDP an effective tool for forecasting.
Keywords :
accounting; economic indicators; genetic algorithms; grey systems; genetic algorithm; global optimization; grey forecast model; grey modeling process; grey system theories; national economic accounting; regional development policy; regional gross national product forecasting; Differential equations; Economic forecasting; Economic indicators; Electronic government; Electronic learning; Genetic algorithms; Information systems; Optimization methods; Predictive models; Technology forecasting; genetic algorithm; grey forecasing t model; optimization; regional gross national product;
Conference_Titel :
E-Learning, E-Business, Enterprise Information Systems, and E-Government, 2009. EEEE '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-3907-2
DOI :
10.1109/EEEE.2009.53
