Method and system for predicting grape downy mildew

Abstract

The embodiment of the invention provides a method and a system for predicting grape downy mildew. The method comprises the following steps of: obtaining data from onset samples of a set of grape samples infected with downy mildew; processing the data from the onset samples to obtain a relational prediction factor based on the grey relational analysis method; inputting the relational prediction factor used as the feature vector of the SVM model, and obtaining the optimal model parameters based on the PSO algorithm to construct a grape downy mildew prediction model; obtaining prediction resultsof grape downy mildew by analyzing grapes infected with downy mildew by using the grape downy mildew prediction model. The prediction method and system provided by the embodiment of the present invention screen out the prediction factors that can better reflect the change trend of grape downy mildew through the grey relational analysis method, and combine the particle swarm optimization algorithmto optimize the model parameters of the support vector machine to establish the grape downy mildew prediction model. The model can quickly and accurately predict the disease grade of grape downy mildew in the short term, can effectively improve prediction accuracy of grape downy mildew, and can provide a basis for disease prevention.

Description

technical field [0001] The invention relates to the field of crop disease prediction, in particular to a grape downy mildew prediction method and system. Background technique [0002] Grape downy mildew is a fungal disease on leaves, which can easily lead to abnormal growth of fruit ears, resulting in reduced yield and serious economic losses. Rapid, accurate and targeted forecasting is the key means to effectively prevent and control the occurrence and development of grape downy mildew, and it is of great significance to ensure high yield, safety and high-quality production of grapes. [0003] At present, the conventional prediction methods for grape downy mildew mainly include judgment methods based on empirical models, system simulation methods, and regression analysis methods. However, in the actual application process, it was found that although the above-mentioned traditional prediction methods played a positive role in the prediction of grape downy mildew within a ce...

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Problems solved by technology

[0006] The embodiment of the present invention provides a grape downy mildew prediction method

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