We present a novel numerical method for solving ordinary differential equations using radial basis function (RBF) network with extreme learning machine algorithm. A single-layer RBF link neural model has been developed the proposed method. The weight from hidden layer to output can be calculated efficiently by experimental comparison of various methods proves that shows better performance than ...

Due to the highly nonlinearity of the flux-linkage characteristics of Switched Reluctance Motor drives (SRM), accurately modelling is cumbersome. In this paper, the offlinetrained and the online-trained Radial Basis function (RBF) neural network model are proposed for estimating the SRM flux-linkage under running conditions. To investigate the performance of the modelling schemes, the simulatio...

In the recent years, new techniques such as; artificial neural networks and fuzzy inference systems were employed for developing of the predictive models to estimate the needed parameters. Soft computing techniques are now being used as alternate statistical tool. Determination of swell potential of soil is difficult, expensive, time consuming and involves destructive tests. In this paper, use ...

have aroused great interest in fi elds as diverse as biology, psychology, medicine, economics, mathematics, statistics and computer science. The main reason underlying this interest lies in the fact that ANN are general, fl exible, nonlinear tools capable of approximating any sort of arbitrary function (Hornik, Stinchcombe, & White, 1989). Due to their fl exibility as function approximators, AN...

Elliptic boundary value problems (BVPs) are widely used in various scientific and engineering disciplines that involve finding solutions to elliptic partial differential equations subject certain conditions. This article introduces a novel approach for solving BVPs using an artificial neural network (ANN)-based radial basis function (RBF) collocation method. In this study, the backpropagation i...

recently, hardware sensors are widely used in monitoring and measurement of water quality parameters. constraint of the instrument to measure some water quality parameters such as the 5-day biochemical oxygen demand (bod5), which are time consuming, causes efforts are diverted to the use of software sensors for online prediction of bod5. the main goal of this research is developing an appropria...

Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

In this paper we summarize various possible techniques such as Crossover Prediction Model or the classical Principal Component Analysis (PCA) tool to include exogenous data. Furthermore we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in ...