Scientia Agricultura Sinica ›› 2012, Vol. 45 ›› Issue (23): 4924-4930.doi: 10.3864/j.issn.0578-1752.2012.23.020

• VETERINARY SCIENCE • Previous Articles     Next Articles

Research on the Combined Forecast Model Method Based on BP Neural Network Improved by Genetic Algorithm

 LIANG  Yi, LIU  Shi-Hong   

  1. Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2012-06-20 Online:2012-12-01 Published:2012-10-29

Abstract: 【Objective】 The combined forecasting model for studying the classic swine fever morbidity was proposed.【Method】The data was processed by ARIMA and GM(1,1) initially, then the results were used as the inputs of the majorizing BP neural network.【Result】The combined model was used to analyze the monthly data from 2000/01 to 2008/05, and the accuracy of the forecasting results from 2008/06 to 2009/06 was 97.379%. The prediction accuracy of the combined model increased by 5.469%, 3.499%, and 1.188%, respectively, compared with BP neural network, ARIMA, GM(1,1), which suggest that the combined model is more steady than traditional methods.【Conclusion】This research has supplied an efficient analytical tool for animals diseases forecasting work, verified the feasibility of the combined model in animal diseases forecasting research, and also has provided references to other animal diseases.

Key words: combined model , ARIMA , GM (1 , 1) , genetic algorithm , BP neural network

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