A Theoretical Study on Event Spreading Prediction by Probabilistic Connectivity Analysis in Dispersive Networks

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dc.authoridAlagoz, Baris Baykant/0000-0001-5238-6433
dc.authoridAlnahas, Dima/0000-0002-6046-1066
dc.authorwosidAlagoz, Baris Baykant/ABG-8526-2020
dc.contributor.authorAlnahas, Dima
dc.contributor.authorAlagoz, Baris Baykant
dc.date.accessioned2024-08-04T20:46:54Z
dc.date.available2024-08-04T20:46:54Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.descriptionInternational Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractThis study discusses a potential use of probabilistic connectivity analysis for prediction of future progresses of events in stochastic network models. Probabilistic relation graphs provide a useful mathematical tool for representation of stochastic network models such as Markov chain models and random transitive networks. These stochastic network models have been widely and effectively used for analysis purpose in a range of application areas (e.g. statistics, language processing, genetics...). In this fashion, the current study investigates applications of the graph connectivity analysis based on taking powers of probabilistic relation matrices. Such probabilistic connectivity analysis can provide knowledge for prediction of future progress of spreading stochastic events in dispersive networks. Some properties of a stochastic dispersive network can be explored by taking power of probabilistic relation matrix, which indeed yields a probabilistic projection for future progress of the network in probability domain. Paper aims to develop a basic understanding for applications of probabilistic connectivity analysis for dispersive networks. Accordingly, applications of this analysis are considered, and illustrative examples are presented for discussion.en_US
dc.description.sponsorshipIEEE Turkey Sect,Anatolian Sci,Inonu Univ, Comp Sci Dept,Inonu Univ, Muhendisli Fakultesien_US
dc.identifier.doi10.1109/idap.2019.8875926
dc.identifier.scopus2-s2.0-85074880141en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/idap.2019.8875926
dc.identifier.urihttps://hdl.handle.net/11616/99030
dc.identifier.wosWOS:000591781100055en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPredictionen_US
dc.subjectMarkov chainen_US
dc.subjecttransitive networksen_US
dc.subjectgraph connectivityen_US
dc.subjectprobabilistic relationen_US
dc.subjectmatrix poweren_US
dc.titleA Theoretical Study on Event Spreading Prediction by Probabilistic Connectivity Analysis in Dispersive Networksen_US
dc.typeConference Objecten_US

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