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51 articles for “Probabilistic model”
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Research ArticleOpen accessIn the abstractModeling A Multi-Compartments Biological System with Membrane ComputingRavie Chandren Muniyandi, Abdullah Mohd. ZinProblem statement: Most of the biological systems have been hierarchical in structure with processes interacting between different compartments. Membrane computing formalism has provided modeling capabilities in representing the structure of biological systems. Approach: This study was carried to investigate the modeling of a multi-compartment biological system by using membrane computing formalism. The hormone-induced calcium oscillations in liver cells which was … …Journal of Computer Science, Vol. 6, Issue 10 · 10 Aug 2010 · 7,256 accessesView PDFCite
Research ArticleOpen accessIn the abstractStochastic Optimization for Portfolio Selection Problem with Mean Absolute Negative Deviation MeasureAnton Abdulbasah Kamil, Adli Mustafa, Khlipah IbrahimProblem statement: The most important character within optimization problem is the uncertainty of the future returns. Approach: To handle such problems, we utilized probabilistic methods alongside with optimization techniques. We developed single stage and two stage stochastic programming with recourse. The models were developed for risk adverse investors and the objective of the stochastic programming models is to minimize the … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 6,947 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm Based Probabilistic Motif Discovery in Unaligned Biological SequencesM. Hemalatha, K. VivekanandanFinding motif in biosequences is the most important primitive operation in computational biology. There are many computational requirements for a motif discovery algorithm such as computer memory space requirement and computational complexity. To overcome the complexity of motif discovery, we propose an alternative solution integrating genetic algorithm and Fuzzy Art machine learning approaches for eliminating multiple sequence alignment process. Problem … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,729 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Neutral Network in Predicting Corporate FailureHuong G. NguyenThis study investigates the predictive power of three neutral network models: Multi-layer neural network, probabilistic neural network, and logistic regression model in predicting corporate failure. Basing on the database provided by The Corporate Scorecard Group (CSG), we combine financial ratios which deem to be significant predictors of corporate bankruptcy in many previous empirical studies to build our predictive models and … …Journal of Social Sciences, Vol. 1, Issue 4 · 31 Dec 2005 · 7,324 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL EMAIL RESPONSE ALGORITHM FOR EMAIL MANAGEMENT SYSTEMSAbdulkareem Al-AlwaniEmail has been one of the most commonly used tool for communication in the recent years and email management has evolved as a major challenge due to prevailing situation of online email congestion. This study presents a novel algorithm for automatic email response methodology in an Email Management System to minimize email overload. The proposed model uses Bayes classifier to … …Journal of Computer Science, Vol. 10, Issue 4 · 23 Dec 2013 · 7,049 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Single Core Hardware Module of a Data Compression Scheme Using Prediction by Partial Matching TechniqueJubayer Jalil, Md. Mamun, Mohd. Marufuzzaman, Hafizah HusainProblem statement: Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space or transmission bandwidth. For effective data compression, the compression algorithm must be able to predict future data accurately in order to build a good probabilistic model for compression. Lossless compression is essential in cases where it is important that the original … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,255 accessesView PDFCite
Research ArticleOpen accessIn the abstractARABIC PART OF SPEECH TAGGING USING K-NEAREST NEIGHBOUR AND NAIVE BAYES CLASSIFIERS COMBINATIONRund Mahafdah, Nazlia Omar, Omaia Al-OmariPart Of Speech (POS) tagging forms the important preprocessing step in many of the natural language processing applications such as text summarization, question answering and information retrieval system. It is the process of classifying every word in a given context to its appropriate part of speech. Different POS tagging techniques in the literature have been developed and experimented. Currently, it … …Journal of Computer Science, Vol. 10, Issue 9 · 2 May 2014 · 7,578 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Spatial-Temporal Variability of Nitrates in a Section of the Cuneo Plain (North West Italy)Massimo Vincenzo Civita, Adriano Fiorucci, Bartolomeo VignaThe study of an aquifer system is very important, but also very complicated because of the high temporal and spatial variabilities of a system and because of the phenomena that are at play within the system. It is from these problems that the necessity arises of finding methods that are able to extend point knowledge to an entire area, while … …American Journal of Environmental Sciences, Vol. 3, Issue 3 · 30 Sep 2007 · 6,729 accessesView PDFCite
Research ArticleOpen accessIn the abstractApproaches for Categorization of Reusable Software ComponentsParvinder Singh Sandhu, Janpreet Singh, Hardeep SinghReuse repositories manager manages the reusable software components in different categories and needs to find the category of reusable software components. In this paper, we have used different pure and hybrid approaches to find the domain relevancy of the component to a particular domain. Probabilistic Latent Semantic Analysis (PLSA) approach, LSA, Singular Value Decomposition (SVD) technique, LSA Semi-Discrete Matrix Decomposition … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,902 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Drug-Target Interaction Prediction Based on Supervised Probabilistic ClassificationManmohan Singh, Susheel Kumar Tiwari, G. Swapna et al.Bayesian ranking-based drug-target relationship prediction has achieved good results, but it ignores the relationship between drugs of the same target. A new method is proposed for drug-target relationship prediction based on groups by Appling Bayesian. According to the reality that drugs interacting with a specific target have similarities, a grouping strategy was introduced to make these similar drugs interact. A … …Journal of Computer Science, Vol. 19, Issue 10 · 1 Sep 2023 · 5,454 accessesView PDFCite