The Animal Diseases Forecast Methods Research And System Implementation

In the present animal breeding process, the damage of Animals pandemic virus, such as classicalswine fever, Newcastle disease, blue ear pig disease, foot-and-mouth disease and so on, became one ofthe most reason that hinder the development of the aquaculture industry, and also brought largeeconomic losses to farming industry. Introduction of species and the environmental degradation makethe prevention and control of animal disease more difficult, at the same time brought a great deal ofdifficulty to the actual forecasting, therefore animal disease monitoring study become an importantmethod to guarantee that farming industry is carried out smoothly. From forecast rely on the experienceof the staff, to the various forecast models, forecasting technology is also in constant progress, as wellas bring a higher demand to guarantee the accuracy and timeliness of forecasting, indeed the accurateanimal disease monitoring and well modeling rationality has become an important indicator for theevaluation of forecasting techniques.This paper takes Classical swine fever epidemic as the research objects, through the analysis of thepathogenesis of classical swine fever, as well as the impact factors of disease indicators, proposes theforecasting system based on combined model. The results from single forecast models afford benefit forthe animal disease forecasting work, which still can’t reach the high accuracy level and satisfy theprecision requirements, and the practical application is insufficient. The combined model is a hotresearch topic in the current forecasting methods, the method combine some single model, and absorbthe advantages of each model of prediction, so this method is better than a single model. This combinedmodel breakthroughs the shortcomings of the traditional model, such as the complex factors and theimbalance of time, which are not building blocks simply. First, by the analysis of a single model, itevaluates the preliminary forecast results; Secondly, by the joint point between the rational analysismodel, to find the right combination, and build the combination model; Finally, by the analysis of thedata of combined model data,to get the forecast results more which is better meet the demand. Thisarticle will be on the basis of the combination model, combining with computer technology and systemsengineering, to develop a practical application of information systems based on.NET frame, envelopingthe model algorithms, which also apply to the practical animal disease forecasting job.This study, which raised issues related to conduct in-depth research and explore, focused on howto build a greater accuracy and stability of forecasting mechanism, and the future objectives of the studyis to apply for more animal epidemic objects and become a comprehensive system, and it is also thetarget to continuously research in the future.