{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:51:28Z","timestamp":1777704688998,"version":"3.51.4"},"reference-count":16,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2020,12,4]]},"abstract":"<jats:p>During the COVID-19 epidemic period, it is essential to strengthen physical exercise and improve the health of the whole people. In this paper, based on genetic algorithm, a fuzzy control system is proposed to dynamically adjust the exercise ability of the bodybuilders under the comprehensive consideration of parameters. Through experiments and data processing, the system obtains bioelectric information related to heart rate, heart rate variability and muscle fatigue of the fitness people in the three states of not fatigue, moderate fatigue and extreme fatigue, establishes fuzzy membership function, and thus establishes personalized fitness information feedback control strategy to maintain moderate fitness intensity. By narrowing the gap between the predicted RPE value based on objective information and the measured RPE, the method provides a unified subjective and objective exercise intensity for the bodybuilders, effectively expands the time of aerobic exercise, and enhances the effect of aerobic exercise. In addition, in order to expand the scope of application of the exercise intensity control model, the service-oriented transformation is carried out to enable it to provide fitness content combinations of interest to fitness practitioners and instructors.<\/jats:p>","DOI":"10.3233\/jifs-189277","type":"journal-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T09:16:13Z","timestamp":1600161373000},"page":"8805-8812","source":"Crossref","is-referenced-by-count":1,"title":["A fuzzy control system for fitness service based on genetic algorithm during COVID-19 pandemic"],"prefix":"10.1177","volume":"39","author":[{"given":"Zhihui","family":"He","sequence":"first","affiliation":[{"name":"Zhengzhou Sias University, Zhengzhou, Henan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Yangtze University, Jingzhou, Hubei, China"},{"name":"Siemens AG, Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-189277_ref1","unstructured":"Linlin L. , Bin Y. , Xiaolin Z. , Zhiqiang Z. , Research on VMI of multi-supplier and multi-retailer based on cultural genetic algorithm, Modern Manufacturing Engineering 2017(2)."},{"key":"10.3233\/JIFS-189277_ref2","first-page":"153","article-title":"Gene expression programming algorithm based on conditional cloud","volume":"2015","author":"Yue","journal-title":"Application Research of Computers"},{"key":"10.3233\/JIFS-189277_ref3","unstructured":"Liangliang J. , Chaoyong Z. , Xinyu S. , Research on integrated process planning and scheduling based on cultural genetic algorithm, Journal of Huazhong University of Science and Technology (Natural Science Edition) 2017(3)."},{"key":"10.3233\/JIFS-189277_ref4","unstructured":"Wei L. , Image segmentation algorithm based on genetic algorithm, Western Leather 2017(8)."},{"issue":"35","key":"10.3233\/JIFS-189277_ref5","first-page":"1534","article-title":"Network traffic feature selection based on mutual information and cultural genetic algorithms","volume":"2014","author":"Changsheng","journal-title":"Journal of Northeastern University: Natural Science Edition"},{"issue":"01","key":"10.3233\/JIFS-189277_ref6","first-page":"42","article-title":"Infrared image contour extraction based on gene expression coding algorithm","volume":"2013","author":"Shuiwang","journal-title":"Infrared Technology"},{"issue":"31","key":"10.3233\/JIFS-189277_ref7","first-page":"251","article-title":"Research on the decision problem of winning bidding in combination auction based on cultural genetic algorithm","volume":"2013","author":"Xiaoping","journal-title":"Value Engineering"},{"issue":"01","key":"10.3233\/JIFS-189277_ref8","first-page":"234","article-title":"A gene selection algorithm based on splitting","volume":"2012","author":"Yongquan","journal-title":"Computer Science"},{"key":"10.3233\/JIFS-189277_ref9","unstructured":"Li L. , Analysis of disease gene prediction algorithm based on network method, Journal of Baoji University of Arts and Sciences (Natural Science Edition) 2017(1)."},{"issue":"02","key":"10.3233\/JIFS-189277_ref10","first-page":"171","article-title":"Advancement learning algorithm based on gene expression programming","volume":"2013","author":"Qian","journal-title":"Computer Technology and Development"},{"issue":"08","key":"10.3233\/JIFS-189277_ref11","first-page":"99","article-title":"Research on image segmentation based on genetic evolution branch tree algorithm[J]","volume":"2013","author":"Baohong","journal-title":"Laser and Infrared"},{"issue":"08","key":"10.3233\/JIFS-189277_ref12","first-page":"88","article-title":"Map Reduce-based improved algorithm for locating gene reads","volume":"2015","author":"Jinjin","journal-title":"Computer Science"},{"issue":"7","key":"10.3233\/JIFS-189277_ref13","first-page":"537","article-title":"Map Reduce-based genetic data density hierarchical clustering algorithm","volume":"2014","author":"Jinjin","journal-title":"Journal of University of Science and Technology of China"},{"issue":"4","key":"10.3233\/JIFS-189277_ref14","first-page":"168","article-title":"Multi-objective differential evolution algorithm based on jumping genes","volume":"2016","author":"Zheng","journal-title":"Computer Engineering"},{"issue":"S1","key":"10.3233\/JIFS-189277_ref15","first-page":"172","article-title":"Calculation of JWL equation of state parameters based on genetic algorithm and \u03b3-law state equation","volume":"2017","author":"Cheng","journal-title":"Journal of Ordnance Engineering"},{"key":"10.3233\/JIFS-189277_ref17","first-page":"154","article-title":"Design of test signals for system identification based on genetic algorithm","volume":"2014","author":"Wei","journal-title":"Henan Science"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-189277","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:41:47Z","timestamp":1777455707000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-189277"}},"subtitle":[],"editor":[{"given":"Xiaolong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2020,12,4]]},"references-count":16,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.3233\/jifs-189277","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,4]]}}}