Prediction of the Trend of Antimicrobial Resistance of Escherichia coli in Livestock and Poultry

摘要

With huge and irrational application of antibiotics, Escherichia coli has gradually formed antimicrobial resistance and the trend is raising. This makes the prevention and control of the disease more complicated. In order to get better control effectof colibacillus and ensure food safety, the trend needs to be predicted. Therefore, this paper proposes a model of prediction of the trend of antimicrobial resistance of Escherichia Coli. The historical data of antimicrobial resistance of Escherichia Coli in pigs in Chengdu .China from 2002 to 2014 was selected as an example. Then, MATLAB was applied to build a gray model, a neural network model and a combined model of Grey-neural network to predict the antimicrobial resistance of Escherichia coli. Compared with the errors of the three prediction models, it was found that the integrated model of Grey and neural network had the smallest error of 13.9%. The results indicated that the integrated model could accurately predict the trend of antimicrobial resistance ofE. coli in livestock and poultry and it is able to benefit to the accurate prevention and treatment of E. coli disease.