Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data...

Due to remarkable capabilities of artificial neural networks (ANNs) such as generalization and nonlinear system modeling, ANNs have been extensively studied and applied in a wide variety of applications (Amiri et al., 2007; Davande et al., 2008). The rapid development of ANN technology in recent years has led to an entirely new approach for the solution of many data processing-based problems, u...

This work addresses an efficient neural network (NN) representation for the phase-field modeling of isotropic brittle fracture. In recent years, data-driven approaches, such as networks, have become active research field in mechanics. this contribution, deep networks—in particular, feed-forward (FFNN)—are utilized directly development failure model. The verification and generalization trained m...

In this paper, a neural network model reference adaptive system speed observer is designed, which can be used in speed control of linear induction motors (LIMs). Dynamical equations of LIM have been considered accurate. In other words, the end effect and the electrical losses of the motor have been included in the motor equivalent circuit. Then equations of the reference model and adaptive mode...

Artificial Neural Networks are information processing systems. Over the past several years, these algorithms have received much attention for their applications in pattern completing, pattern matching and classification and also for their use as a tool in various areas of problem solving. In this work, an Artificial Neural Network model is presented for predicting the tensile properties of co...

Neural network, as a fundamental classification algorithm, is widely used in many image classification issues. With the rapid development of high performance computing device and parallel computing devices, convolutional neural network also draws increasingly more attention from many researchers in this area. In this project, we deduced the theory behind back-propagation neural network and impl...

Energy performance analysis in buildings is becoming more and highlighted, due to the increasing trend of energy consumption building sector. Many studies have declared great potential soft computing for this analysis. A particular methodology sense employing hybrid machine learning that copes with drawbacks single methods. In work, an optimized version a popular model, namely feed-forward neur...

the incremental sheet metal forming (ismf) process is a new and flexible method that is well suited for small batch production or prototyping. this paper studies the use of the finite element method in the incremental forming process of aa1050 sheets to investigate the influence of tool diameter, vertical step size, and friction coefficient on forming force, spring-back, and thickness distribut...

in this article, the effect of operating conditions, such as temperature, gas hourly space velocity (ghsv), ch4/o2 ratio and diluents gas (mol% n2) on ethylene production by oxidative coupling of methane (ocm) in a fixed bed reactor at atmospheric pressure was studied over mn/na2wo4/sio2 catalyst. based on the properties of neural networks, an artificial neural network was used for model develo...