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85 articles for “Artificial Neural Network (BP-ANN)”
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Research ArticleOpen accessIn the abstractEvaluation of Artificial Immune System with Artificial Neural Network for Predicting Bombay Stock Exchange TrendsM. Gunasekaran, K. S. RamaswamiProblem statement: The purpose of this study is to develop an artificial immune system for recognizing stock market trends and predict upward and downward directions of stock market. This study compared two prediction models, an Artificial Immune System (AIS) and Artificial Neural Network (ANN) for predicting the future index value, trend of Indian stock market and discovers the best prediction … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural NetworkN. Narmadhai, A. Ebenezer JeyakumarProblem statement: The phenomenon of flashover in polluted insulators has been continued by the study of the characteristics of contaminating layers deposited on the surface of insulators in high voltage laboratories. In the literature, Experimental investigations have been carried out on a real insulator or a flat plate model of insulators under high voltage application. This study proposed the Equivalent … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,624 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomating Commercial Video Game Development using Computational IntelligenceTse Guan Tan, Jason Teo, Patricia AnthonyProblem statement: The retail sales of computer and video games have grown enormously during the last few years, not just in United States (US), but also all over the world. This is the reason a lot of game developers and academic researchers have focused on game related technologies, such as graphics, audio, physics and Artificial Intelligence (AI) with the goal … …American Journal of Economics and Business Administration, Vol. 3, Issue 1 · 31 Jan 2011 · 7,623 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Behavior of an Artificial Neural Network Defined on Multipartite Directed GraphN. C. Majee, A. B. RoyProblem statement: Artificial Neural Network (ANN) are simple models to mimic some essential features of the complex central nervous system. ANN models are realistic due to their inherent stochastic nature of neural computation and strong synchronicity. Different ANN models are associated with directed and signed graphs. The present study proceeded by relaxing certain simplifying assumptions in the ANN model. Approach: … …OnLine Journal of Biological Sciences, Vol. 10, Issue 1 · 30 Jun 2010 · 7,479 accessesView PDFCite
Research ArticleOpen accessIn the abstractCreep predicting model in masonry structure utilizing dynamic neural networkMustafa M. Abed, A. El-Shafie, Siti Aminah Bt. OsmanProblem statement: When the loads are applied to a brickwork structure, visco-elastic behavior upon their stress-strain relationships is exhibited, where the response can be classified into two separate parts: an instantaneous elastic strains and time-dependent creep strains. The creep strain represents the non- instantaneous strain that happens with time when the stress is sustained. Through the previous century, along with … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,631 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach to Classify Noises in Images Using Artificial Neural NetworkT. Santhanam, S. RadhikaProblem statement: Noise identification is predominant in any digital image processing algorithms, which helps in identifying the filters to smooth the image for further processing. Approach: An Artificial Neural Network (ANN) based approach was proposed for noise identification. The suggested technique involved seclusion of the noise samples and extracts their statistical features, which was then applied to a neural network … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,192 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Network Based Model for Forecasting Sugar Cane ProductionO. O. Obe, D. K. ShangodoyinProblem statement: The global need for alternative energy source has necessitated the exploration of vast organic agricultural products with a view of processing them for the production of ethanol in commercial quantity. To ascertain a sustainable production of ethanol from processed sugar cane, a predictive model based on non-linearity nature of its production is imperative. This is due to unavailability … …Journal of Computer Science, Vol. 6, Issue 4 · 30 Apr 2010 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Method for Fetal Electrocardiogram Extraction from the Abdominal Electrocardiogram SignalMuhammad Asraful Hasan, Muhammad Ibn Ibrahimy, Mamun Bin Ibn ReazProblem statement: FECG (Fetal Electrocardiogram) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labor. Approach: Conventional techniques were often unable to achieve the extraction of FECG from the Abdominal ECG (AECG) in satisfactorily level. A new methodology by combining the Artificial Neural Network (ANN) and Correlation (ANNC) approach had … …Journal of Computer Science, Vol. 5, Issue 9 · 30 Sep 2009 · 7,356 accessesView PDFCite
Research ArticleOpen accessIn the abstractANN Based Prediction of Effect of Reinforcements on Abrasive Wear Loss and Hardness in a Hybrid MMCP. Sathyabalan, V. Selladurai, P. SakthivelProblem statement: The reinforcements added to an alloy lead to variation in properties. The content and size of the reinforcement influences the properties of composites. Very little research has been carried out in hybrid composites. Work on hybrid LM6 aluminium alloy metal matrix composites (MMC) with flyash and SiC has been initiated here. The effect of the four parameters, size … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 1 · 31 Mar 2009 · 7,558 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of Sulfur Dioxide (SO2) Concentration Levels from the Mina Al-Fahal Refinery in Oman Using Artificial Neural NetworksSabah A. Abdul-Wahab, Saleh M. Al-AlawiIn this investigation, two Artificial Neural Network (ANN) models were applied for predicting ground-level sulfur dioxide (SO2) in the Sultanate of Oman in order to provide an early warning advisory for the protection of public health. The objective of the first model (Model I) was to use ANN to predict sulfur dioxide (SO2) levels at certain receptors from the Mina … …American Journal of Environmental Sciences, Vol. 4, Issue 5 · 31 Oct 2008 · 7,391 accessesView PDFCite