Predicting the Tensile Properties of UV Degraded Nylon66/Polyester Woven Fabric Using Regression and Artificial Neural Network Models
نویسندگان
چکیده
منابع مشابه
The Prediction of the Tensile Strength of Sandstones from their petrographical properties using regression analysis and artificial neural network
This study investigates the correlations among the tensile strength, mineral composition, and textural features of twenty-ninesandstones from Kouzestan province. The regression analyses as well as artificial neural network (ANN) are also applied to evaluatethe correlations. The results of simple regression analyses show no correlation between mineralogical features and tensile strength.However,...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
investigation of thermal comfort properties of woven sport fabric using blend of estabragh fibers
امروزه لباس در نظر ورزشکاران و کسانی که برای اوقات فراغت خود و یا برای رسیدن به اندامی متعادل، ورزش می کنند؛ بسیار با اهمیت است. احساس مطلوب از لباس در زمره خصوصیات راحتی پوشش می باشد. خصوصیات انتقال رطوبت لباس، در ارزیابی راحتی حسی و حرارتی منسوجات تولید شده از آن ها بسیار مهم است. هدف از این تحقیق، معرفی پارچه جدید است که متشکل از الیاف استبرق با خواص منحصر به فرد می باشد. استبرق لیف طبیعی تو...
Artificial Neural Network Techniques in Identifying Plain Woven Fabric Defects
Textile industry is one of the main sources of revenue generating industry. The price of fabrics is severely affected by the defects of fabrics that represent a major threat to the textile industry. In manual inspection a very small percentage of defects are detected with highly trained, experienced inspectors. An automatic defect detection system can increase the defect detection percentage. I...
متن کاملEVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS
In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Engineered Fibers and Fabrics
سال: 2015
ISSN: 1558-9250,1558-9250
DOI: 10.1177/155892501501000101