Construction And Research Of Rice Disease Control Model Based On Knowledge Graph

As a big rice production country,rice production in China shoulders the important task of grain stability in China,and it is also one of the important sources of farmers' income.However,rice diseases have been endangering the safe and stable yield and increasing production of rice.With the study of rice disease prevention and control,important progress has been made in regional integrated rice disease control,expert system and other aspects,but there is a lack of rice disease prevention and control model combined with meteorological factors and other non-infectious factors.Therefore,it is of great significance to study the model of rice disease prevention and control by using artificial intelligence(AI)technology to study the non-invasive factors.Then the rice disease control scheme was retrieved by adding weight value according to the influence degree of non-invasive factors on rice diseases by constructing the non-invasive factors of rice diseases as self-built index.On the basis of the above,the rice disease reasoning model is constructed.The prediction value of support vector machine is retrieved and matched with the case index of knowledge graph,and the disease correlation calculation and disease accuracy calculation are carried out on the matching value.Accurate disease types were obtained.Finally,the shortest path algorithm is applied to optimize the disease retrieval path,and the rice disease control scheme is obtained.The results show that the prediction model based on the knowledge graph(non-infective factors),which is based on the knowledge graph(non-infective factors),is integrated with the support vector machine classification and prediction,and the control scheme for the rice disease is put forward,and the results show that the prediction model established by the previous data processing has a good generalization effect.It has the value of application and popularization.