The architecture fusion of human motor nerve and neural network computer driven by sports

Ren, Xiaojian

doi:10.3233/jifs-179175

Cited by 1 publication

(3 citation statements)

References 14 publications

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“…In order to reduce the randomness of the input vector, the data should be normalized to a value in the range of [0,1] before input. It is necessary to use logarithms or error functions to improve the regularity of the data [ 18 , 19 ]. We need to standardize the input vector with the following function:

where y min , y max represent the minimum value and the maximum value in the input vector of the i th unit; μ , v are the parameters, where 2 μ + v =1, and

represents the normalized input vector.…”

Section: Methodsmentioning

confidence: 99%

“…In order to reduce the randomness of the input vector, the data should be normalized to a value in the range of [0,1] before input. It is necessary to use logarithms or error functions to improve the regularity of the data [18,19]. We need to standardize the input vector with the following function:…”

Section: Public Physical Health Knowledge Discovery and Decisionmentioning

confidence: 99%

“…Fitness events ref [15] ref [19] Our ref [18] Figure 5: Performance comparison of different sports video recognition models.…”

Section: Table Tennis Badminton Volleyballmentioning

confidence: 99%

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Feasibility Study of Mass Sports Fitness Program Based on Neural Network Algorithm

2022

Computational Intelligence and Neuroscience

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Mass sports has become a world trend, setting off a new health revolution in the world. Mass fitness programs not only enrich people's lives. It not only relieves the psychological pressure of modern people but also promotes people's health and improves people's quality of life. According to the time-consuming stability of neural network algorithm, this paper proposes a sports video recognition algorithm based on BP neural network. The static and dynamic features are classified by BP neural network, and the basic probability assignment is constructed according to the preliminary recognition results. At the same time, we use evidence theory to fuse the preliminary results and get the results of motion video recognition. It can be applied to the generation model of the feasible scheme of mass sports fitness. Relevant experiments show that the whole model that generates the feasible mass sports fitness scheme can accurately generate the sports fitness scheme of multiple patient users and ensure the rationality and safety of the sports fitness scheme.

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where y min , y max represent the minimum value and the maximum value in the input vector of the i th unit; μ , v are the parameters, where 2 μ + v =1, and

represents the normalized input vector.…”

Section: Methodsmentioning

confidence: 99%

“…In order to reduce the randomness of the input vector, the data should be normalized to a value in the range of [0,1] before input. It is necessary to use logarithms or error functions to improve the regularity of the data [18,19]. We need to standardize the input vector with the following function:…”

Section: Public Physical Health Knowledge Discovery and Decisionmentioning

confidence: 99%

See 1 more Smart Citation

Feasibility Study of Mass Sports Fitness Program Based on Neural Network Algorithm

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

The architecture fusion of human motor nerve and neural network computer driven by sports

Cited by 1 publication

References 14 publications

Feasibility Study of Mass Sports Fitness Program Based on Neural Network Algorithm

Feasibility Study of Mass Sports Fitness Program Based on Neural Network Algorithm

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