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298 results for “neural networks”
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Research ArticleOpen accessPhrase in the titleAnalysis of Time-Delayed Neural Networks via Rightmost Eigenvalue PositionsSun Yi, Sangseok Yu, Jung H. Kim, Taher M. Abu-LebdehNeural networks have been frequently used in various areas. In the implementation of the networks, time delays and uncertainty are present and known to lead to complex behaviors, which are hard to predict using classical analysis methods. In this study, stability and robust stability of neural networks considering time delays and parametric uncertainty is studied. For stability analysis, the rightmost … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 26 Jan 2015 · 8,057 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePREDICTION OF FIGHT OR FLIGHT RESPONSE USING ARTIFICIAL NEURAL NETWORKSAbhijit Suresh, Sai Swarna Latha, Pooja Nair, N. RadhikaThe modern society has posed several threats to the public. Public security is declining with increasing anti-social behaviour. Cases of rape and terrorist attacks have become increasingly common and there is a strong demand for a security system to control such modalities. Anti-social behaviour is a key issue of public concern. Public perceptions, however, have been improving recently. The vital … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 3 Apr 2014 · 8,041 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleLICENSE PLATE LOCALIZATION USING GABOR FILTERS AND NEURAL NETWORKSSami Ktata, Faouzi Benzarti, Hamid AmiriVehicle License Plate Detection (LPD) is an important step for the vehicle plate recognition which can be used in the intelligent transport systems. Many methods have been proposed for the detection of license plates based on: Mathematical morphology, Discrete Wavelet Transform, Hough Transform and others. In general, an LPR system includes four main parts: Vehicle image acquisition, license plate detection, … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,977 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA NOVEL APPROACH BASED ON GENETIC FUZZY CLUSTERING AND ADAPTIVE NEURAL NETWORKS FOR SALES FORECASTINGAttariuas Hichama, Bouhorma Mohameda, El Fallahi AbdellahbThis article proposes a new hybrid sales forecasting system based on genetic fuzzy clustering and Back-Propagation (BP) Neural Networks with adaptive learning rate (GFCBPN).The proposed architecture consists of three stages: (1) utilizing Winter’s Exponential Smoothing method and Fuzzy C-Means clustering, all normalized data records will be categorized into k clusters; (2) using an adapted Genetic Fuzzy System (MCGFS), the fuzzy … …Journal of Computer Science, Vol. 9, Issue 8 · 2 Jul 2013 · 6,669 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,792 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAttack of Against Simplified Data Encryption Standard Cipher System Using Neural NetworksKhaled M. Alallayah, Waiel F. Abd El-Wahed, Mohamed Amin, Alaa H. AlhamamiProblem statement: The problem in cryptanalysis can be described as an unknown and the neural networks are ideal tools for black-box system identification. In this study, a mathematical black-box model is developed and system identification techniques are combined with adaptive system techniques, to construct the Neuro-Identifier. Approach: The Neuro-Identifier was discussed as a black-box model to attack the target cipher … …Journal of Computer Science, Vol. 6, Issue 1 · 31 Jan 2010 · 7,941 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleGeneralization Aspect of Neural Networks on Upgrading Assimilation Structure into Accommodating SchemeWaleed, A. J. Rasheed, Hamza A. AliProblem statement: Generalization feature enhancement of neural networks, especially feed forward structural model has limited progress. The major reason behind such limitation is attributed to the principal definition and the inability to interpret it into convenient structure. Traditional schemes, unfortunately have regarded generalization as an innate outcome of the simple association, referred to by Pavlov and had been modeled by … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,149 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDynamic 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 accessPhrase in the titleDesign of a Neural Networks Classifier for Face DetectionF. Smach, M. Atri, J. Mitéran, M. AbidFace detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation allows real-time processing, but has higher cost and time to-market. The objective of this work was to implement a classifier based on neural networks MLP (Multi-layer Perception) for face detection. The … …Journal of Computer Science, Vol. 2, Issue 3 · 31 Mar 2006 · 6,885 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleConsumer Choice Prediction: Artificial Neural Networks versus Logistic ModelsChristopher Gan, Visit Limsombunchai, Mike Clemes, Amy WengConventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. The purpose of this paper is to empirically compare the predictive power of the probability neural … …Journal of Social Sciences, Vol. 1, Issue 4 · 31 Dec 2005 · 8,441 accessesView PDFCite