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51 results for “Probabilistic model”
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Research ArticleOpen accessIn the abstractQuantifying Business Process Optimization using RegressionGezani Richman Miyambu, Solly Matshonisa SeeletseThe paper applies regression methods to model Business Process Optimisation (BPO) in order to derive measures for the extent of BPO achievement if efforts to optimise have already started. This will help to identify components of business that still need to be improved if full optimisation has not yet been achieved in a business. Regression methods were used to explain … …American Journal of Applied Sciences, Vol. 12, Issue 12 · 25 Nov 2015 · 6,629 accessesView PDFCite
Research ArticleOpen accessIn the abstractProposed Reliability Techniques on Soil and Rock ExcavationsS. TangchawalProblem statement: Assessment of the ground mass excavation is normally done by the deterministic method. A quantitative indication of mass stability provides as an index term known "the Factor of Safety (F.S.)". There are uncertain to some degrees, such as only a single value of mass properties is used or variation in geologic conditions, computed values of F.S. are never … …Energy Research Journal, Vol. 2, Issue 1 · 26 Jan 2012 · 7,413 accessesView PDFCite
Research ArticleOpen accessIn the abstractMembrane Computing as a Modeling Tool for Discrete SystemsRavie Chandren Muniyandi, Abdullah Mohd. ZinProblem statement: Discrete systems have been modeled by using Ordinary Differential Equation (ODE) in which the variation of concentration of an object was modeled as continuous and deterministic manner, contrary to the real behaviors of such systems. Although, this approaches able to generate the general behavior of the system, the specific discrete processes and stochastic behaviors in the system have … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,796 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 · 6,950 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 · 7,052 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 · 7,258 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 · 7,583 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 · 6,733 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 · 6,906 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 · 5,463 accessesView PDFCite