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Swimming athlete training load prediction method based on PCA-PNN

A technology of training load and prediction method, which is applied in sports accessories, neural learning methods, biological neural network models, etc., can solve the problems of not giving full play to the important role of coaches, and the training load arrangement is not complete and reliable, so as to reduce the complexity of the network , the effect of fast training convergence speed and high prediction accuracy

Active Publication Date: 2020-09-18
江苏第二师范学院
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Problems solved by technology

[0003] However, the existing training load arrangement for swimmers does not have a complete and reliable framework, and does not give full play to the important role of excellent coaches in popularizing scientific swimming sports training. Therefore, the applicant designs a swimmer training based on PCA-PNN load forecasting method

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  • Swimming athlete training load prediction method based on PCA-PNN
  • Swimming athlete training load prediction method based on PCA-PNN
  • Swimming athlete training load prediction method based on PCA-PNN

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Embodiment Construction

[0035] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0036] The invention provides a PCA-PNN-based swimmer training load prediction method. The method constructs a swimmer's training load prediction model to evaluate a swimmer's training arrangement by studying the influence of the athlete's training load on fusion features.

[0037] As a specific embodiment of the present invention, this application provides a PCA-PNN based swimmer training load prediction method framework such as figure 1 As shown, the PNN prediction network model based on the comprehensive feature index is as follows figure 2 shown.

[0038] Step1: feature index selection and database construction;

[0039]The present invention selects the characteristic indexes of the load forecasting model from three aspects, which are the swimmer's basic information data, training data and physiological and biochemical data. There are 5 ...

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Abstract

The invention discloses a swimming athlete training load prediction method based on PCA-PNN. The method comprises the steps: step 1, carrying out feature index selection and database construction; step 2, carrying out principal component analysis to construct a PNN network input quantity; and step 3, constructing a PNN swimming athlete training load prediction model. The invention provides the swimming athlete training load prediction method based on PCA-PNN; the method constructs the swimming athlete training load prediction model through the research of the training load impact fusion features of an athlete, so as to evaluate the training arrangement of one swimming athlete.

Description

technical field [0001] The invention belongs to the field of athlete training load prediction methods, in particular to a PCA-PNN-based swimmer training load prediction method. Background technique [0002] In competitive swimming, the development of athletes' competitive ability depends not only on whether the selection method of athletes is scientific, but also on whether the training methods and methods during years of training are reasonable, and whether the exercise load is properly arranged. Training is an important daily content in an athlete's career. Athletes can improve their competitive level through reasonable training, but too much training will cause injuries to athletes, and too little training will not achieve the training effect. At the same time, if the same training method and load arrangement are used for athletes in different states, then the training will not have the desired effect, and even if it is excessive, it will cause damage to the technique and...

Claims

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Application Information

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IPC IPC(8): A63B69/12G06N3/04G06N3/08
CPCA63B69/12G06N3/08G06N3/045G06N3/047
Inventor 田磊周近
Owner 江苏第二师范学院
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