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28 articles for “Bayesian network”
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Research ArticleOpen accessPhrase in the titleKnowledge Based Bayesian Network Construction Algorithm for Medical Data Fusion to Enhance Services and DiagnosisAhmed SamehTraditional Bayesian networks' algorithms are treating the network construction process as an isolated and autonomous data-driven trial-and-error process and completely ignoring the domain knowledge. In this work we are proposing a new 'Semantically Aware Ontology-Based Bayesian Network construction algorithm' that is knowledge centered instead of data centered. The objective of the new algorithm is to empower patients through improving their … …Journal of Computer Science, Vol. 15, Issue 5 · 28 May 2019 · 8,043 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFuzzy Method for Online Learning of Bayesian Network ParametersMariana D.C. Lima, Silvia M. NassarIn learning problems, there are situations where training data is not fully available at the learning time. They are incrementally generated by time, defining a type of domain called online that has among its characteristics the possibility of data failure or even missing data. In Bayesian networks, learning is divided into two categories: structure (related to the graph of conditional … …Journal of Computer Science, Vol. 15, Issue 3 · 16 Mar 2019 · 7,502 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,247 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBayesian Network Inference in Binary Logistic Regression: A Case Study of Salmonella sp Bacterial Contamination on Vannamei ShrimpPratnya Paramitha Oktaviana, Kartika FithriasariRecently binary logistic regression has been used to identify four factors or predictor variables that supposedly influence the response variable, which is testing result of Salmonella sp bacterial contamination on vannamei shrimp. Binary logistic regression analysis results that there are two predictor variables which is significantly affect the testing result of Salmonella sp bacterial contamination on vannamei shrimp, those are … …Journal of Mathematics and Statistics, Vol. 13, Issue 4 · 22 Dec 2017 · 7,673 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHEURISTIC DISCRETIZATION METHOD FOR BAYESIAN NETWORKSMariana D.C. Lima, Silvia M. Nassar, Pedro Ivo R.B.G. Rodrigues et al.Bayesian Network (BN) is a classification technique widely used in Artificial Intelligence. Its structure is a Direct Acyclic Graph (DAG) used to model the association of categorical variables. However, in cases where the variables are numerical, a previous discretization is necessary. Discretization methods are usually based on a statistical approach using the data distribution, such as division by quartiles. In … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 7,059 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDynamic Bayesian Networks in Classification-and-Ranking Architecture of Response GenerationAida Mustapha, Md. Nasir Sulaiman, Ramlan Mahmod, Mohd. Hasan SelamatProblem statement: The first component in classification-and-ranking architecture is a Bayesian classifier that classifies user utterances into response classes based on their semantic and pragmatic interpretations. Bayesian networks are sufficient if data is limited to single user input utterance. However, if the classifier is able to collate features from a sequence of previous n-1 user utterances, the additional information may … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,106 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModeling of Piezoelectric Actuators Based on Bayesian Regularization Back Propagation Neural NetworkWen Wang, Zhu Zhu, Yanding Wei, Zichen ChenProblem statement: Piezoelectric actuator is a kind of key driving components for micropositioning stages, micropumps, micro valves, micro gripper and so on in the fields of micro/nano technology such as integrated circuit manufacturing, precision instruments, ultra precision fabrication, biomedical manipulation. It has lots of advantages including high stiffness, fast response times, less heat generating, low power consumption and large force … …Current Research in Nanotechnology, Vol. 1, Issue 1 · 15 Jun 2011 · 7,064 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Enhancement of Bayesian Inference Network for Ligand-Based Virtual Screening using Features SelectionAli Ahmed, Ammar Abdo, Naomie SalimProblem statement: Similarity based Virtual Screening (VS) deals with a large amount of data containing irrelevant and/or redundant fragments or features. Recent use of Bayesian network as an alternative for existing tools for similarity based VS has received noticeable attention of the researchers in the field of chemoinformatics. Approach: To this end, different models of Bayesian network have been developed. … …American Journal of Applied Sciences, Vol. 8, Issue 4 · 18 Apr 2011 · 7,724 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFrom Feature Selection to Building of Bayesian Classifiers: A Network Intrusion Detection PerspectiveKok-Chin Khor, Choo-Yee Ting, Somnuk-Phon AmnuaisukProblem statement: Implementing a single or multiple classifiers that involve a Bayesian Network (BN) is a rising research interest in network intrusion detection domain. Approach: However, little attention has been given to evaluate the performance of BN classifiers before they could be implemented in a real system. In this research, we proposed a novel approach to select important features by … …American Journal of Applied Sciences, Vol. 6, Issue 11 · 30 Nov 2009 · 7,076 accessesView PDFCite