Research ArticleOpen accessIn the abstractPecan Weevil Recognition Using Support Vector Machine MethodGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: The Pecan weevil was considered as the most dangerous pest of Pecan fruits. The aim of this research is to evaluate Support Vector Machine method (SVM) for identifying Pecan Weevil among other insects. Eventually, this recognition system will serve in a wireless imaging network for monitoring Pecan Weevils. Approach: SVM has been evaluated using two different kernel functions … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 4 · 24 Dec 2011 · 7,926 accessesView PDFCite
Research ArticleOpen accessIn the abstractRBFNN Model for Predicting Nonlinear Response of Uniformly Loaded Paddle CantileverAbdullah H. AbdullahThe Radial basis Function neural network (RBFNN) model has been developed for the prediction of nonlinear response for paddle Cantilever with built-in edges and different sizes, thickness and uniform loads. Learning data was performed by using a nonlinear finite element program, incremental stages of the nonlinear finite element analysis were generated by using 25 schemes of built paddle Cantilevers with … …American Journal of Applied Sciences, Vol. 6, Issue 1 · 31 Jan 2009 · 7,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Analysis of Structures Using Neural NetworksN. Ahmadi, R. Kamyab Moghadas, A. LavaeiIn the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR) and Back-Propagation Wavenet neural network (BPW), for approximating of dynamic time history response of … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,154 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Rainfall-runoff Models to Zard River Catchment'sM. B. Rahnama, G. A. BaraniRainfall-runoff models are nonlinear processes according to the sequential and spatial distribution of the rainfall. So, it is difficult to explain the response of catchments systems with the simple models. In the present work simulation of the rainfall-runoff processes have been carried out by the Artificial Neural Networks (ANN) and the HEC-HMS models. The ANN models of Multi Layer Perceptron … …American Journal of Environmental Sciences, Vol. 1, Issue 1 · 31 Mar 2005 · 6,528 accessesView PDFCite