STLF is used in making decisions about economical power generation capacity, fuel purchasing, safety assessment, and power system planning in order to have economical power conditions. In this study, Turkey’s 24-hourahead load forecasting without meteorological data is studied. ANN, wavelet transform and ANN, wavelet transform and RBF NN, and EMD and RBF NN structures are used in STLF procedure...

Artificial neural network (ANN) based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multil...

The response surface methodology (RSM), which typically uses quadratic polynomials, is predominantly used for metamodeling in crashworthiness optimization because of the high computational cost of vehicle crash simulations. Research shows, however, that RSM may not be suitable for modeling highly nonlinear responses that can often be found in impact related problems, especially when using limit...

The common use of an artificial neural network model has been in water resources management and planning. length, width, discharge a basin were measured this study utilizing field data from 160 Dashti Hawler existing projects. Multilayer Perceptron (MLP) Radial Basic Function (RBF) networks employed the irrigation assessment. Input factors included soil type, conveyance system effectiveness, ro...

background: diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. the aim of this study was to determine the predictive precision of the bivariate logistic regression (lr) and artificial neutral network (ann) in concurrent diagnosis of diabetes and hypertension. methods: this cross-sectional study was performed with 12000 ira...

In this paper an ANN model is developed to forecast the monthly inflation of Bangladesh as a function of its own previous value. The model selects a feed-forward backpropagation ANN with two inputs, one hidden layer with five hidden neurons and one output as the optimum network. The model is tested with actual time series data of inflation in case of Bangladesh and forecast evaluation criteria....

One of the principal issues related to hydrologic models for prediction of runoff is the estimation of extreme values (floods). It is well understood that unless the models capture the dynamics of rainfall-runoff process, the improvement in prediction of such extremes is far from reality. In this paper, it is proposed to develop a dual (combined and paralleled) artificial neural network (D-ANN)...

This paper, two Artificial Neural Network (ANN) models using radial basis function (RBF) nets are developed for the design of Aperture Coupled Microstrip Antennas (ACMSA) for different number of design parameters. The effect of increasing the number of design parameters on the ANN model is also discussed in this work. The performances of the models when compared are found that on decreasing the...

The improvement of the accuracy of image query retrieval used image classification technique. Image classification is well known technique of supervised learning. The improved method of image classification increases the working efficiency of image query retrieval. For the improvements of classification technique we used RBF neural network function for better prediction of feature used in image...

genetic algorithm and partial least square (ga-pls), the kernel pls (kpls) and levenberg-marquardt artificial neural network (l-m ann) techniques were used to investigate the correlationbetween retention time (rt) and descriptors for 15 nanoparticle compounds which obtained by thecomprehensive two dimensional gas chromatography system (gc x gc). application of thedodecanethiol monolayer-protect...