Athlete pre-competition state evaluation method based on multi-cycle evolution entropy technology

Abstract

The invention relates to an athlete pre-competition state evaluation method based on a multi-cycle evolution entropy technology, and belongs to the field of data processing. According to the method, historical competition data of an athlete is processed according to different attributes, and the entropy of athlete state data and the attribute entropy of an athlete item are obtained; the comprehensive entropy of the athlete state data under each attribute is established, and the attribute with the maximum comprehensive entropy is selected as the first classification level of the decision tree; then, in several pieces of data to be classified determined under the first classification hierarchy, comprehensive entropies under residual attributes are respectively solved, and a second classification hierarchy of the decision tree is selected according to a principle that the comprehensive entropies are maximum; and so on, until the decision tree is constructed; and finally, the competition result of the athlete after n cycles is predicted by combining the decision-making tree with the attribute condition of the pre-competition state data of the athlete. The method can objectively predict competition winning and losing results of the athletes, and is high in accuracy and good in market application prospect.

Description

technical field [0001] The invention belongs to the field of data processing, and in particular relates to a method for evaluating athletes' pre-match state based on multi-period evolution entropy technology. Background technique [0002] In sports majors, athletes are usually divided into training players and competitive players. The former refers to players who perform well during training, but tend to perform abnormally in competitions. The latter refers to players who perform averagely during training, but are usually able to perform super long when it comes to competitions. The mental state of the athletes before the competition is the root cause of this phenomenon. Psychological factors can largely affect the results of the competition, but they are difficult to quantify. Only the coach can predict the results of the athletes’ competitions in advance based on subjective experience. Therefore, The prediction accuracy of the athletes' game winners and losers is low and ...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a multi-period evolutionary entropy technology-based evaluation method for athletes' pre-match status, which is used to solve the problem of low accuracy of existing methods in predicting athletes' game results based on subjective experience

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