Presentation | 2002/3/8 A Prediction System with Layered-type Neural Networks for Periodization Tsutomu YOSHIDA, Takao YAMAMOTO, Kenya JIN'NO, Haruo HIROSE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A training schedule is very important factor for efficient muscular training. The total training schedule is called "Periodization." For Periodization, if a system can predict training results, such prediction system is useful for motivation improvement of a training person. In this article, we propose such prediction system which uses a layered-type neural network. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | layered-type neural network / back propargation algorithm / predioction system / periodization / muscular training |
Paper # | NLP2001-112 |
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Conference Information | |
Committee | NLP |
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Conference Date | 2002/3/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Prediction System with Layered-type Neural Networks for Periodization |
Sub Title (in English) | |
Keyword(1) | layered-type neural network |
Keyword(2) | back propargation algorithm |
Keyword(3) | predioction system |
Keyword(4) | periodization |
Keyword(5) | muscular training |
1st Author's Name | Tsutomu YOSHIDA |
1st Author's Affiliation | Department of Electrical and Electronics Engineering, Nippon Institute of Technology() |
2nd Author's Name | Takao YAMAMOTO |
2nd Author's Affiliation | Department of Electrical and Electronics Engineering, Nippon Institute of Technology |
3rd Author's Name | Kenya JIN'NO |
3rd Author's Affiliation | Department of Electrical and Electronics Engineering, Nippon Institute of Technology |
4th Author's Name | Haruo HIROSE |
4th Author's Affiliation | Department of Electrical and Electronics Engineering, Nippon Institute of Technology |
Date | 2002/3/8 |
Paper # | NLP2001-112 |
Volume (vol) | vol.101 |
Number (no) | 723 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |