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111 articles for “Artificial Neural Networks”

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Research ArticleOpen accessIn the abstractINTRUSION DETECTION SYSTEM IN SECURE SHELL TRAFFIC IN CLOUD ENVIRONMENTMehdi Barati, Azizol Abdullah, NurIzura Udzir et al.Due to growth of Cloud computing usage, the need to apply encrypted protocols to provide confidentiality and integrity of data increases dramatically. Attacker can take advantage of these protocols to hide the intrusion and evade detection. Many traditional attack detection techniques have been proposed to provide security in the networks but none of them can be implemented properly in encrypted … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 7,856 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE ANALYSIS OF OPTIMIZATION TECHNIQUES FOR ARTIFICIAL NEURAL NETWORK IN BIO MEDICAL APPLICATIONSV. Saishanmuga Raja, S. P. RajagopalanIn this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm (GA) Particle Swarm Optimization (PSO) and Ant-Colony Optimization (ACO) which are used to optimize the Artificial Neural Network (ANN). Optimization of Neural Networks improves speed of recall and may also improve the efficiency of training. Here we have used the Ant colony optimization, Particle Swarm … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 7,291 accessesView PDFCite
Research ArticleOpen accessIn the abstractA REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEMSutarman, Mazlina Abdul Majid, Jasni Mohamad ZainSign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: … …Journal of Computer Science, Vol. 9, Issue 11 · 27 Sep 2013 · 8,698 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid of Fuzzy Clustering Neural Network Over NSL Dataset for Intrusion Detection SystemDahlia Asyiqin Ahmad Zainaddin, Zurina Mohd HanapiIntrusion Detection System (IDS) is one of the component that take part in the system defence, to identify abnormal activities happening in the computer system. Nowadays, IDS facing composite demands to defeat modern attack activities from damaging the computer systems. Anomaly-Based IDS examines ongoing traffic, activity, transactions and behavior in order to identify intrusions by detecting anomalies. These technique identifies … …Journal of Computer Science, Vol. 9, Issue 3 · 4 May 2013 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimal Control Algorithms for Second Order SystemsDanilo Pelusi, Raffaele MascellaProportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,034 accessesView PDFCite
Research ArticleOpen accessIn the abstractMammogram Analysis Based on Pixel Intensity Mean FeaturesR. Nithya, B. SanthiProblem statement: In the recent years, Computer Aided Diagnosis (CAD) can be very useful for detection of breast cancer. Mammography can be used as an efficient tool for breast cancer diagnosis. A computer based diagnosis and classification system can reduce unnecessary biopsy. Approach: This study investigates a new approach to the classification of mammogram images based on pixel intensity mean … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 7,670 accessesView PDFCite
Research ArticleOpen accessIn the abstractCerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation ErrorOlatubosun Olabode, Bola Titilayo OlabodeProblem statement: Most important problems of medical diagnosis. When there is a cerebrovascular accident attach the chances of a successful treatment depends essentially on the early diagnosis. In practice the part of medical errors while diagnosing a stroke type comes to 20-45% even for experienced doctors and the scope of methods of neurovisualization at stroke diagnosis are limited. Approach: In … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,335 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded ChannelP. Sivakumar, N. Chithra, S. N. Sivanandam, M. RajaramProblem statement: Digital transmission over band-limited communication channel largely suffers from ISIS and various noise sources. The presence of ISI and noise causes bit errors in the received signal. Equalization is necessary at the receiver to overcome these channel impairment to recover the original transmitted sequence. Traditionally equalization is considered as equivalent to inverse filtering and implemented using linear-perform under … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 6,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Neuro-Fuzzy Techniques for Solar RadiationW. A. Rahoma, U. Ali Rahoma, A. H. HassanProblem statement: The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. Approach: The forecasting ability of some models could be further enhanced with … …Journal of Computer Science, Vol. 7, Issue 10 · 11 Aug 2011 · 7,080 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network in Modeling Malaysian Oil Palm YieldZuhaimy Ismail, Azme KhamisProblem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN). The main issue in yield forecasting is to … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 8,581 accessesView PDFCite