Crop yield prediction method based on machine learning

Abstract

The invention relates to a crop yield prediction method based on machine learning. Climatic characteristics in a crop growth period are utilized; through machine learning, relevance between climatic characteristics and crop yield is established, different learning models are trained by utilizing historical data, and the current year yield is predicted in combination with current meteorological information characteristics, so that agricultural employees can know yield information in time, and a basis is provided for agricultural production decisions. Three different machine learning classification algorithms are integrated to predict the crop yield, and integrated judgment is carried out on the prediction result, so that the problem of poor robustness of a single learning algorithm is reduced, and the accuracy and credibility of the prediction result are improved. And more timely and accurate yield prediction can be easily realized, and necessary technical support is provided for realizing grain yield production and decision making.

Description

technical field [0001] The invention relates to the technical field of crop yield prediction, in particular to a machine learning-based crop yield prediction method. Background technique [0002] my country is a large agricultural country, and grain production has been increasing year after year. Agricultural production and production methods have entered a new stage, and new requirements for agricultural production have also emerged. In agricultural production, issues such as focusing on the quality of agricultural products and the early warning capabilities of agricultural disasters has become an urgent need. my country's agricultural planting management mode has been constantly changing from "big agriculture" to "small agriculture", and refined production has also put forward higher requirements for corresponding agricultural equipment. What came into being is to judge the growth status of crops, Forecast crop yields. [0003] Crop yield is easily affected by different me...

AI Technical Summary

Problems solved by technology

How to predict the crop yield separately, and make an integrated judgment on the prediction results, so as to reduce the problem of poor robustness of a single learning algorithm, and improve the accuracy and reliability of the prediction results is the focus of the research of the present invention

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