Prediction of soil unconfined compressive strength using Artificial Neural Network Model
نویسندگان
چکیده
منابع مشابه
Prediction of ultimate strength of shale using artificial neural network
A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research work, using the artificial neural network (ANN), a model was built to predict the ultimat...
متن کاملPrediction of Pervious Concrete Permeability and Compressive Strength Using Artificial Neural Networks
Pervious concrete is a concrete mixture prepared from cement, aggregates, water, little or no fines, and in some cases admixtures. The hydrological property of pervious concrete is the primary reason for its reappearance in construction. Much research has been conducted on plain concrete, but little attention has been paid to porous concrete, particularly to the analytical prediction modeling o...
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 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...
PREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS
Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, artificial neural networks (ANN) for predicting compressive strength of cubes and durability of concrete containing metakaolin with fly ash and silica fume with fly ash are developed at the age of 3, 7, 28, 56 and 90 days. For building these...
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: VIETNAM JOURNAL OF EARTH SCIENCES
سال: 2020
ISSN: 0866-7187,0866-7187
DOI: 10.15625/0866-7187/42/3/15342