Prediction System Of Main Wheat Diseases In Hebei Province Based On BP Neural Network

Wheat is the main food crop in China.It is vulnerable to scab,powdery mildew,rust,sheath blight and other important diseases in the growth process,which affect the yield and quality of wheat.If the control is not timely,it will easily cause serious economic losses.Timely and accurate prediction of the occurrence of wheat diseases is of great significance to the formation of an efficient prevention and control system for wheat diseases.The system mainly uses PHP technology to realize the prediction of wheat diseases.Based on WebGIS platform,Baidu map is used to show the incidence level of wheat diseases.ECharts technology is used to analyze and display the prediction results of wheat diseases and realize visualization.Using GIS to realize regional positioning,it is easy to observe the incidence trend intuitively.By using BP neural network algorithm,this paper designs a prediction model of Wheat Main Diseases in Hebei Province,taking wheat scab as an example.The disease grade is divided into four grades,and the occurrence of the disease is predicted and simulated.Visual display of the disease is realized at the terminal.It is convenient for the plant protection department to formulate the corresponding prevention and control plan to ensure wheat yield and increase farmers' income.The main work is as follows:Firstly,system analysis and design,the system uses modular design,the whole system is divided into front-end information display and backstage management,frontend map area display;the predicted disease results and real results are compared,disease area and planting area over the years are compared.Backstage management has data analysis,display and user information management.Secondly,Establish a prediction model based on BP neural network.In the information display,the meteorological environmental factors of wheat are analyzed.First,the data of previous times are selected as samples,and then BP neural network algorithm is used to process the prediction model,and then other data are predicted.The model will be trained according to the selected sample data,and the self-adaptive ability will be used to adjust automatically until the conditions are met,and then other data will be used to detect to ensure reliability.Thirdly,visualization of disease prediction is realized.The results are displayed on Baidu map through the prediction model.Using thermodynamic chart to visualize the severity grade and area of the disease,the loss degree can be estimated as a whole and the visualization effect can be achieved.In order to prevent and control the disease in the affected areas and further expand the area of disease control.Fourthly,ECharts technology is used to display the test results in order to facilitate intuitive analysis,to predict the occurrence of wheat diseases in the future by analyzing the occurrence law of wheat diseases,using ECharts technology to show the effect of the model,as well as the regularity of disease area and condition factors.The design and development of this system provides an efficient technical tool for the prediction and prediction of major diseases of wheat.It is an organic combination of information processing technology and agricultural disease prevention.It is an effective way to solve wheat disease prediction by using computer technology.