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    Wyświetlanie 1-6 z 6
    Tytuł:
    Research on the image design of clothing patterns
    Autorzy:
    Chen, Daoling
    Cheng, Pengpeng
    Tematy:
    clothing pattern
    image design
    Kansei engineering
    quantitative class I theory
    personalized customization
    Pokaż więcej
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Powiązania:
    https://bibliotekanauki.pl/articles/59115073.pdf  Link otwiera się w nowym oknie
    Opis:
    In order to solve the problem of mismatch between consumers’ personalized needs and clothing pattern design, a method of clothing pattern image design was proposed based on Kansei engineering theory to obtain a perceptual consumer image. Then, a correlation model between clothing pattern design elements and perceptual images of young people was established through the quantitation theory type I, and the mapping relationship between the two and the degree of influence on consumer preference was presented by the diagram method. The paper-cut pattern of a T shirt is taken as an example to verify the feasibility of this research method. The results show that it not only provides designers with clear design indicators and references, but also makes the design process more objective and scientific.
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on the image design of clothing patterns
    Autorzy:
    Cheng, Pengpeng
    Chen, Daoling
    Wydawca:
    Sciendo
    Cytata wydawnicza:
    Chen, D. & Cheng, P. Research on the image design of clothing patterns. Fibres & Textiles in Eastern Europe, 2024, Sciendo, vol. 32 no. 1, pp. 17-24. https://doi.org/10.2478/ftee-2024-0003
    Opis:
    This paper was supported by 2023 Fujian Provincial Social Science Foundation project (FJ2023B081), 2023 Minjiang University Faishu Charity Foundation Donated Funds Research Project (No. MFS23010), 2022 Fujian Province Education Science “Fourteen Fifth Plan” Project (No. FJJKBK22-011) and 2022 Minjiang University teaching research and construction project (No. MJUCJJG2022005).
    In order to solve the problem of mismatch between consumers’ personalized needs and clothing pattern design, a method of clothing pattern image design was proposed based on Kansei engineering theory to obtain a perceptual consumer image. Then, a correlation model between clothing pattern design elements and perceptual images of young people was established through the quantitation theory type I, and the mapping relationship between the two and the degree of influence on consumer preference was presented by the diagram method. The paper-cut pattern of a T shirt is taken as an example to verify the feasibility of this research method. The results show that it not only provides designers with clear design indicators and references, but also makes the design process more objective and scientific.
    Dostawca treści:
    Repozytorium Centrum Otwartej Nauki
    Artykuł
    Tytuł:
    Temperature and Humidity Data Evaluation of Tight Sportswear During Motion Based on Intelligent Modeling
    Autorzy:
    Cheng, Pengpeng
    Wang, Jianping
    Zeng, Xianyi
    Bruniaux, Pascal
    Chen, Daoling
    Tematy:
    motion state
    tight sportswear
    temperature
    humidity
    prediction model
    Pokaż więcej
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Powiązania:
    https://bibliotekanauki.pl/articles/24200969.pdf  Link otwiera się w nowym oknie
    Opis:
    A neural network structure of Long Short Term Memory (LSTM) is proposed which could be used to predict the temperaturę 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 temperaturę 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.
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent Prediction Model of the Thermal and Moisture Comfort of the Skin-Tight Garment
    Autorzy:
    Cheng, Pengpeng
    Wang, Jianping
    Zeng, Xianyi
    Bruniaux, Pascal
    Chen, Daoling
    Tematy:
    sportswear tights
    thermal comfort
    moisture comfort
    principal component analysis
    intelligent prediction model
    Pokaż więcej
    Wydawca:
    Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
    Powiązania:
    https://bibliotekanauki.pl/articles/2056304.pdf  Link otwiera się w nowym oknie
    Opis:
    In order to improve the efficiency and accuracy of predicting the thermal and moisture comfort of skin-tight clothing (also called skin-tight underwear), principal component analysis (PCA) is used to reduce the dimensions of related variables and eliminate the multicollinearity relationship among variables. Then, the optimized variables are used as the input parameters of the coupled intelligent model of the genetic algorithm (GA) and back propagation (BP) neural network, and the thermal and moisture comfort of different tights (tight tops and tight trousers) under different sports conditions is analysed. At the same time, in order to verify the superiority of the genetic algorithm and BP neural network intelligent model, the prediction results of GA-BP, PCA-BP and BP are compared with this model. The results show that principal component analysis (PCA) improves the accuracy and adaptability of the GA-BP neural network in predicting thermal and humidity comfort. The forecasting effect of the PCA-GA-BP neural network is obviously better than that of the GA-BP, PCA-BP, BP model, which can accurately predict the thermal and moisture comfort of tight-fitting sportswear. The model has better forecasting accuracy and a simpler structure.
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent Prediction Model of the Thermal and Moisture Comfort of the Skin-Tight Garment
    Autorzy:
    Chen, Daoling
    Zeng, Xianyi
    Wang, Jianping
    Bruniaux, Pascal
    Cheng, Pengpeng
    Wydawca:
    Łukasiewicz - Łódzki Instytut Technologiczny
    Cytata wydawnicza:
    Cheng P, Wang J, Zeng X, Bruniaux P, Chen D. Intelligent Prediction Model of the Thermal and Moisture Comfort of the Skin-Tight Garment. FIBRES & TEXTILES in Eastern Europe 2022; 30, 1(151): 50-58. DOI: 10.5604/01.3001.0015.6461
    Opis:
    This paper was financially supported by the China Scholarship Council.
    In order to improve the efficiency and accuracy of predicting the thermal and moisture comfort of skin-tight clothing (also called skin-tight underwear), principal component analysis(PCA) is used to reduce the dimensions of related variables and eliminate the multicollinearity relationship among variables. Then, the optimized variables are used as the input parameters of the coupled intelligent model of the genetic algorithm (GA) and back propagation (BP) neural network, and the thermal and moisture comfort of different tights (tight tops and tight trousers) under different sports conditions is analysed. At the same time, in order to verify the superiority of the genetic algorithm and BP neural network intelligent model, the prediction results of GA-BP, PCA-BP and BP are compared with this model. The results show that principal component analysis (PCA) improves the accuracy and adaptability of the GA-BP neural network in predicting thermal and humidity comfort. The forecasting effect of the PCA-GA-BP neural network is obviously better than that of the GA-BP, PCA-BP, BP model, which can accurately predict the thermal and moisture comfort of tight-fitting sportswear. The model has better forecasting accuracy and a simpler structure.
    Dostawca treści:
    Repozytorium Centrum Otwartej Nauki
    Artykuł
    Tytuł:
    Temperature and Humidity Data Evaluation of Tight Sportswear During Motion Based on Intelligent Modeling
    Autorzy:
    Chen, Daoling
    Cheng ,Pengpeng
    Zeng, Xianyi
    Wang, Jianping
    Bruniaux, Pascal
    Wydawca:
    Sciendo
    Cytata wydawnicza:
    Cheng P, Wang J, Zeng X, Bruniaux P, Chen D. Temperature and Humidity Data Evaluation of Tight Sportswear during Motion Based on Intelligent Modeling. Fibres & Textiles in Eastern Europe. Sciendo, 2023;31}(3): 1-8. https://doi.org/10.2478/ftee-2023-0021
    Opis:
    The authors would like to acknowledge the financial support from the International Cooperation Fund of Science and Technology Commission of Shanghai Municipality(Grant NO. 21130750100) and Fujian Province Social Science Planning Project(FJ2020C049)
    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.
    Dostawca treści:
    Repozytorium Centrum Otwartej Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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