In this study, an artificial neural network (ANN) approach was employed for modeling the moisture absorption (MA) and thickness swelling (TS) properties of oriented strand board (OSB) in various applications. A series of ANN models were developed for the analysis and prediction of correlations between processing parameters and MA and TS of OSB. An ANN model was found for modeling the effects of...

injection molding is one of the most important and common plastic formation methods. combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...

the quantitative structure-retention relationship (qsrr) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. the genetic algorithm (ga) was employed to select the variables that resulted in the best-fitted models. after the variables were selected, the linear multi...

The modeling of the energy storage system (ESS) of a Hybrid Electric Vehicle (HEV) poses a considerable challenge. The problem is not amenable to physical modeling without simplifying assumptions that compromise the accuracy of such models. An alternative is to build conventional empirical models. Such models, however, are time-consuming to build and are dataintensive. In this paper, we demonst...

this paper shows that the use the optimal topology of an Artificial Neural Network (ANN) for a particular application is one of the difficult tasks. Neural Network is optimized by a Genetic Algorithm (GA), in a hybrid technique, to calculate the multiplicity distribution of the charged shower particles on Larger Hadron Collider (LHC). Moreover, ANN, as a machine learning technique, is usually u...

This paper introduces a new concept of integrating artificial neural networks (ANN) and genetic algorithms (GA) in modeling the deflection basins measured on the flexible pavements. Backcalculating pavement layer moduli are well-accepted procedures for the evaluation of the structural capacity of pavements. The ultimate aim of the backcalculation process from Nondestructive Testing (NDT) result...

This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent co...

In this paper an accurate nonlinear model of induction motor using an artificial neural network (ANN) is given. This modeling technique is done by using the data from the system inputs/outputs information without requiring the knowledge about machine parameters. The ANN training is carried out off-line using the Levenberg-Marquardt algorithm. Then, the proposed neural network model is used as p...

In resent years ANN is widely reported for modeling in different areas of science including electro chemistry. This includes modeling of different technological batteries such as lead acid battery, Nickel cadmium batteries etc. Lithium ion batteries are advance battery technology which satisfy most of the space mission requirements. Low earth orbit (LEO)space craft batteries undergo large numbe...