Journal of Systems & Management ›› 2022, Vol. 31 ›› Issue (1): 159-166.DOI: 10.3969/j.issn.1005-2542.2022.01.015

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Intelligent Generation of Personalized Exercise Scheme Based on Fuzzy Petri Nets

LIU Yuchuan, ZHANG Pengzhu   

  1. Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China
  • Online:2022-01-28 Published:2022-01-20

基于模糊Petri网的个性化运动方案智能生成

刘宇川,张朋柱   

  1. 上海交通大学 安泰经济与管理学院,上海 200030
  • 作者简介:刘宇川(1995-),男,硕士。研究方向为管理信息系统、智能健康管理
  • 基金资助:
    国家自然科学基金资助项目(91646205,71421002);上海交通大学中央高校基本科研业务费资助项目(16JCCS08)

Abstract: An intelligent generation mechanism based on fuzzy Petri nets is proposed in order to provide a scientific personalized exercise scheme for different users based on their health information. Following FITT(Frequency-Intensity-Time-Type) principle, the mechanism constructs fuzzy Petri nets of exercise frequency, intensity, time and type respectively based on large scale of exercise knowledge. Users’ personalized information is fused for generation of exercise scheme and matrix calculation is adopted. The exercise type is the first to be generated, based on which exercise time, intensity and frequency are also generated. Different exercise schemes are then combined according to users’ willingness. In the end, a complete and operable personalized exercise scheme is formed.

Key words: personalized, exercise scheme, FITT principle, fuzzy Petri nets

摘要: 为了生成针对不同用户个体的个性化科学运动方案,一个基于模糊Petri网的个性化运动方案智能生成方法被提出。该方法遵循FITT(Frequency-Intensity-Time-Type)原则,依据大规模运动知识构造运动类型、运动时间、运动频率、运动强度模糊Petri网,结合个体的个性化信息,以矩阵运算形式进行智能推理。首先推理生成个性化运动类型,在此基础上进一步推理个性化的运动时间、频率和强度,然后基于个体意愿对不同运动类型的运动方案进行组合,最终形成一套完备且可操作性高的个性化运动方案。

关键词: 个性化, 运动方案, FITT原则, 模糊Petri网

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