با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
دسته بندی:
یادگیری ماشین - machine learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Prediction and validation of alternative fillers used in micro surfacing mix-design using machine learning techniques
ترجمه فارسی عنوان مقاله:
پیش بینی و اعتبارسنجی از پرکننده های جایگزین مورد استفاده در طراحی میکرو سطحی با استفاده از تکنیک های یادگیری ماشین
منبع:
Sciencedirect - Elsevier - Construction and Building Materials, 207 (2019) 519-527: doi:10:1016/j:conbuildmat:2019:02:136
نویسنده:
Rajesh Gujar a, Vinay Vakharia b,⇑
چکیده انگلیسی:
In this study regression analysis using machine learning models was investigated to predict and validate
the composition of alternative mineral filler in micro surfacing mix design. To generate the data, 168
experiments were conducted with mixing time (sec), cohesion (30 min) kg.cm, cohesion (60 min) kg.
cm, set time (sec), wet track abrasion loss (g/m2) as an additives for the design of alternative fillers such
as Copper Slag, Fly Ash and High Calcium Fly Ash. Training and testing of feature vector which were
formed after conducting experiment was fed into machine learning regression models for prediction of
composition of fillers. Support vector machine with polynomial, radial basis function and PUK kernel,
Artificial neural network with RBF kernel and Isotonic regression models were considered in the present
study. Machine learning regression models were evaluated using three parameters Correlation coefficient,
Spearman rho’s and Mean absolute error. Excellent agreement between regression models and
experimental results observed. The methodology used will be useful for prediction of micro surfacing
mix design for alternative fillers used in the construction industry.
Keywords: Micro surfacing | Mineral fillers | Machine learning | Support vector machine | Artificial neural network
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0