Research ArticleOpen accessIn the abstractImproved Statistical Speech Segmentation Using Connectionist ApproachM. S. Salam, Dzulkifli Mohamad, S. H. SallehProblem statement: Speech segmentation is an important part for speech recognition, synthesizing and coding. Statistical based approach detects segmentation points via computing spectral distortion of the signal without prior knowledge of the acoustic information proved to be able to give good match, less omission but lot of insertion. These insertion points dropped segmentation accuracy. Approach: This study proposed a fusion … …Journal of Computer Science, Vol. 5, Issue 4 · 30 Apr 2009 · 7,687 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Network Approach in Radar Target ClassificationN.K. Ibrahim, R.S.A. Raja Abdullah, M.I. SaripanProblem statement: This study unveils the potential and utilization of Neural Network (NN) in radar applications for target classification. The radar system under test is a special of it kinds and known as Forward Scattering Radar (FSR). In this study the target is a ground vehicle which is represented by typical public road transport. The features from raw radar signal … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 9,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractBack Propagation Neural Network Arabic Characters Classification Module Utilizing Microsoft WordA. A. HamzaProblem statement: Arabic character recognition has been one of the last major languages to receive attention. This may be attributed to the inherent complexity of both printed and handwritten Arabic characters. The objectives of this study were to: (i) summarize the main characteristics of Arabic language writing style. (ii) suggest a neural network recognition circuit. Approach: A Neural network with … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 7,834 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransient Stability Assessment of a Power System Using Probabilistic Neural NetworkNoor Izzri Abdul Wahab, Azah MohamedThis study presents transient stability assessment of electrical power system using Probabilistic Neural Network (PNN) and principle component analysis. Transient stability of a power system is first determined based on the generator relative rotor angles obtained from time domain simulation outputs. Simulations were carried out on the IEEE 9-bus test system considering three phase faults on the system. The data … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,029 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Hidden Layer Neurons on the Classification of Optical Character Recognition Typed Arabic NumeralsNidal F. Shilbayeh, Mahmoud Z. IskandaraniProblem statement: The effect of varying the number of nodes in the hidden layer and number of iterations are important factors in the recognition rate. In this paper, a novel and effective criterion based on Cross Pruning (CP) algorithm is proposed to optimize number of hidden neurons and number of iterations in Multi Layer Perceptron (MLP) neural based recognition system. … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,561 accessesView PDFCite
Research ArticleOpen accessIn the abstractVulnerability Assessment of Power System Using Radial Basis Function Neural Network and a New Feature Extraction MethodAhmed M.A. Haidar, Azah Mohamed, Aini HussainVulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimensionality reduction of … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 7,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractFunctional Link Artificial Neural Network for Classification Task in Data MiningB. B. Misra, S. DehuriIn solving classification task of data mining, the traditional algorithm such as multi-layer perceptron takes longer time to optimize the weight vectors. At the same time, the complexity of the network increases as the number of layers increases. In this study, we have used Functional Link Artificial Neural Networks (FLANN) for the task of classification. In contrast to multiple layer … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 60,801 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 · 6,535 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnergy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural NetworkAssefa M. Melesse, Rodney S. HanleyA multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN) back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux) were used for training (calibration) and testing (verification) of model outputs. The 15-days … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,349 accessesView PDFCite