This paper introduces a novel design for handwritten letter recognition by employing a hybrid back-propagation neural network with an enhanced evolutionary algorithm. Feeding the neural network consists of a new approach which is invariant to translation, rotation, and scaling of input letters. Evolutionary algorithm is used for the global search of the search space and the back-propagation alg...

Reliable prediction of sales can improve the quality of business strategy. In this research, fuzzy logic and artificial neural network are integrated into the fuzzy back-propagation network (FBPN) for sales forecasting in Printed Circuit Board (PCB) industry. The fuzzy back propagation network is constructed to incorporate production-control expert judgments in enhancing the model’s performance...

there is little consensus on the corporate diversification-efficiency relationship in the diversification literature. according to the corporate diversification, firms have a tendency to get more market share with diversifying in the local segment or in the international market. theoretically, a contradictory exists between the profitable strategy and the value reducing strategy in the diversif...

in this study, activated sludge process for wastewater treatment in a refinery was investigated. for such purpose, a laboratory scale rig was built. the effect of several parameters such as temperature, residence time, effect of leca (filling-in percentage of the reactor by leca) and uv radiation on cod removal efficiency were experimentally examined. maximum cod removal efficiency was obtained...

this research intends to develop a method based on the artificial neural network (ann) to predict permanent earthquake-induced deformation of the earth dams and embankments. for this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. in order to predict earthquake-induced deformation o...

it is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. hence, at present study, two models including artificial neural networks and nonlinear multivariate regression were used to predict peak discharge in taleghan watershed. maximum daily mean discharge and corresponding daily rainfall, one day antecedent and...

In recent years, the studies on literacy and reading have been taken seriously. A lot of researchers mention that t he key factor to improve the students’ reading ability is word recognition. If teachers realize the ability of students’ vocabulary, they can use remedial teaching to help the sub-standard students. This study uses the back-propagation neural network to es tablish an experimental ...

Several approaches for the diagnosis of faults in analog circuits have reasonably accuracy which comes at the cost of heavier processing requirements and lowered efficiencies. In this paper, we propose a time domain based technique for fault diagnosis using specifications extracted from the step response of a circuit. With the help of neural network we have to go for back propagation learning p...

In this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the Shabestar Plain, Iran. After initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (GA-BP) should be able to reproduce groundwater ...

In this study, colorimetric calibration of scanner has been done via perceptron neural network with three or four layers by back propagation algorithm for colored polyester fabrics. The results obtained for random training samples are not satisfactory but application of selective training samples for L*a*b* or RGB leads to good results, with better results obtained for the L*a*b* method. On the...