Proposing a new precise price forecasting method is still challenging task as electricity signals generally exhibit various complex features. In this paper, approach for called hybrid local general regression neural network, and harmony search algorithm (LGRNN-HSA) proposed. The proposed LGRNN-HSA developed by combining the coordinate delay (CD) method, paradigm, network (GRNN) (HSA). CD employ...

abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

Porosity is one of the key parameters associated with oil reservoirs. Determination of this petrophysical parameter is an essential step in reservoir characterization. Among different linear and nonlinear prediction tools such as multi-regression and polynomial curve fitting, artificial neural network has gained the attention of researchers over the past years. In the present study, two-dimensi...

One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...