Pengpeng Cheng, Jianping Wang, Xianyi Zeng, P. Bruniaux, Daoling Chen
{"title":"基于智能建模的紧身运动服运动过程温湿度数据评估","authors":"Pengpeng Cheng, Jianping Wang, Xianyi Zeng, P. Bruniaux, Daoling Chen","doi":"10.2478/ftee-2023-0021","DOIUrl":null,"url":null,"abstract":"Abstract A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperature and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.","PeriodicalId":12309,"journal":{"name":"Fibres & Textiles in Eastern Europe","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Temperature and Humidity Data Evaluation of Tight Sportswear during Motion Based on Intelligent Modeling\",\"authors\":\"Pengpeng Cheng, Jianping Wang, Xianyi Zeng, P. Bruniaux, Daoling Chen\",\"doi\":\"10.2478/ftee-2023-0021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperature and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.\",\"PeriodicalId\":12309,\"journal\":{\"name\":\"Fibres & Textiles in Eastern Europe\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fibres & Textiles in Eastern Europe\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.2478/ftee-2023-0021\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATERIALS SCIENCE, TEXTILES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fibres & Textiles in Eastern Europe","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.2478/ftee-2023-0021","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, TEXTILES","Score":null,"Total":0}
Temperature and Humidity Data Evaluation of Tight Sportswear during Motion Based on Intelligent Modeling
Abstract A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperature and humidity of other key parts from the temperature and humidity data of some parts of the human body when wearing tight sportswear, so as to realize the temperature and humidity data prediction of all key points of the human body. The temperature and humidity of different people wearing tights were collected by DHT sensors. The experimental results show that the LSTM neural network structure proposed has higher prediction accuracy than other algorithms, and the model evaluates the feasibility of temperature and humidity data of tights in a state of motion, which facilitates the study of dynamic thermal and humid comfort and reduces the time cost of analyzing the temperature and humidity distribution and changing the law during human movement. It will effectively promote the study of temperature and humidity changes when people wear sports tights, provide theoretical reference for the study of human skin temperature in the field of sports medicine, and provide practical guidance for the application of human skin temperature changes in sports clothing production, diagnosis and prevention of sports injuries.
期刊介绍:
FIBRES & TEXTILES in Eastern Europe is a peer reviewed bimonthly scientific journal devoted to current problems of fibre, textile and fibrous products’ science as well as general economic problems of textile industry worldwide. The content of the journal is available online as free open access.
FIBRES & TEXTILES in Eastern Europe constitutes a forum for the exchange of information and the establishment of mutual contact for cooperation between scientific centres, as well as between science and industry.