Wheat stripe rust predicting method based on particle swarm and support vector machine

Abstract

The invention discloses a wheat stripe rust predicting method based on a particle swarm and a support vector machine. The method comprises the steps that a stepwise regression method is used for carrying out effective dimension reduction on a high-dimensional sample firstly to eliminate redundancy and reduce the influence of incoherent factors on a forecast object; then the advantages that a PSO algorithm is not likely to fall into local minima, simple in algorithm and small in calculation amount are utilized for optimizing the kernel function parameter g and the penalty factor C of the support vector machine, and an optimal prediction model is obtained fast and efficiently. The method is based on a stepwise regression, PSO and SVM mixed algorithm, wheat stripe rust is accurately and stably predicted and forecast, and a scientific basis is provided for earlier prevention and treatment of wheat stripe rust.

Description

technical field [0001] The invention belongs to the technical field of agricultural disease prevention and control, in particular to a method for predicting wheat stripe rust based on particle swarm and support vector machine. Background technique [0002] Wheat stripe rust is the first major disease affecting wheat production in my country. It has the characteristics of wide occurrence area, strong outbreak, high epidemic frequency, and heavy damage loss. 20%, and it can reach more than 30% in severe epidemic areas, and some areas even fail to harvest, which seriously threatens the safety of wheat production in my country. Therefore, it is very important to carry out the research on the forecasting method of wheat stripe rust, accurately predict the incidence and epidemic trend of wheat stripe rust, and change the passive prevention and control to the active prevention and control in advance. It is very important to guide farmers to effectively control and reduce unnecessary...

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a kind of wheat stripe rust prediction method based on particle swarm and support vector machine. The function parameter g, using the optimized support vector machine to classify and predict the incidence level of wheat stripe rust, is used to solve the problem of low prediction accuracy, overfitting, poor generalization ability and difficulty in determining the initial parameters of the traditional wheat stripe rust prediction model And other issues

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