FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2564602076> ?p ?o ?g. }

• W2564602076 endingPage "590" @default.
• W2564602076 startingPage "558" @default.
• W2564602076 abstract "Carrying out self-diagnosis of telecommunication networks requires an understanding of the phenomenon of fault propagation on these networks. This understanding makes it possible to acquire relevant knowledge in order to automatically solve the problem of reverse fault propagation. Two main types of methods can be used to understand fault propagation in order to guess or approximate as much as possible the root causes of observed alarms. Expert systems formulate laws or rules that best describe the phenomenon. Artificial intelligence methods consider that a phenomenon is understood if it can be reproduced by modeling. We propose in this paper, a generic probabilistic modeling method which facilitates fault propagation modeling on large-scale telecommunication networks. A Bayesian network (BN) model of fault propagation on gigabit-capable passive optical network-fiber to the home (GPON-FTTH) access network is designed according to the generic model. GPON-FTTH network skills are used to build structure and approximatively determine parameters of the BN model so-called expert BN model of the GPON-FTTH network. This BN model is confronted with reality by carrying out self-diagnosis of real malfunctions encountered on a commercial GPON-FTTH network. Obtained self-diagnosis results are very satisfying and we show how and why these results of the probabilistic model are more consistent with the behaviour of the GPON-FTTH network, and more reasonable on a representative sample of diagnosis cases, than a rule-based expert system. With the main goal to improve diagnostic performances of the BN model, we study and apply expectation maximization algorithm in order to automatically fine-tune parameters of the BN model from real data generated by a commercial GPON-FTTH network. We show that the new BN model with optimized parameters reasonably improves self-diagnosis previously carried out by the expert Bayesian network model of the GPON-FTTH access network." @default.
• W2564602076 created "2017-01-06" @default.
• W2564602076 creator A5005509861 @default.
• W2564602076 creator A5034622791 @default.
• W2564602076 creator A5040932898 @default.
• W2564602076 creator A5043368712 @default.
• W2564602076 creator A5043411973 @default.
• W2564602076 date "2016-12-31" @default.
• W2564602076 modified "2023-10-14" @default.
• W2564602076 title "Model-Based Probabilistic Reasoning for Self-Diagnosis of Telecommunication Networks: Application to a GPON-FTTH Access Network" @default.
• W2564602076 cites W1491873892 @default.
• W2564602076 cites W1494646875 @default.
• W2564602076 cites W1549217920 @default.
• W2564602076 cites W1564425416 @default.
• W2564602076 cites W1585839963 @default.
• W2564602076 cites W1587731148 @default.
• W2564602076 cites W1604617515 @default.
• W2564602076 cites W1820739428 @default.
• W2564602076 cites W1893178561 @default.
• W2564602076 cites W1992249670 @default.
• W2564602076 cites W2078712199 @default.
• W2564602076 cites W2124952481 @default.
• W2564602076 cites W2132434674 @default.
• W2564602076 cites W2159826343 @default.
• W2564602076 cites W2161415693 @default.
• W2564602076 cites W2162139012 @default.
• W2564602076 cites W2218478556 @default.
• W2564602076 cites W2525357194 @default.
• W2564602076 doi "https://doi.org/10.1007/s10922-016-9401-0" @default.
• W2564602076 hasPublicationYear "2016" @default.
• W2564602076 type Work @default.
• W2564602076 sameAs 2564602076 @default.
• W2564602076 citedByCount "3" @default.
• W2564602076 countsByYear W25646020762019 @default.
• W2564602076 countsByYear W25646020762020 @default.
• W2564602076 countsByYear W25646020762021 @default.
• W2564602076 crossrefType "journal-article" @default.
• W2564602076 hasAuthorship W2564602076A5005509861 @default.
• W2564602076 hasAuthorship W2564602076A5034622791 @default.
• W2564602076 hasAuthorship W2564602076A5040932898 @default.
• W2564602076 hasAuthorship W2564602076A5043368712 @default.
• W2564602076 hasAuthorship W2564602076A5043411973 @default.
• W2564602076 hasBestOaLocation W25646020762 @default.
• W2564602076 hasConcept C121332964 @default.
• W2564602076 hasConcept C127313418 @default.
• W2564602076 hasConcept C154945302 @default.
• W2564602076 hasConcept C160724564 @default.
• W2564602076 hasConcept C162324750 @default.
• W2564602076 hasConcept C165205528 @default.
• W2564602076 hasConcept C175444787 @default.
• W2564602076 hasConcept C175551986 @default.
• W2564602076 hasConcept C204827203 @default.
• W2564602076 hasConcept C21922175 @default.
• W2564602076 hasConcept C2776330181 @default.
• W2564602076 hasConcept C31258907 @default.
• W2564602076 hasConcept C33724603 @default.
• W2564602076 hasConcept C41008148 @default.
• W2564602076 hasConcept C49040817 @default.
• W2564602076 hasConcept C49937458 @default.
• W2564602076 hasConcept C6260449 @default.
• W2564602076 hasConcept C76155785 @default.
• W2564602076 hasConceptScore W2564602076C121332964 @default.
• W2564602076 hasConceptScore W2564602076C127313418 @default.
• W2564602076 hasConceptScore W2564602076C154945302 @default.
• W2564602076 hasConceptScore W2564602076C160724564 @default.
• W2564602076 hasConceptScore W2564602076C162324750 @default.
• W2564602076 hasConceptScore W2564602076C165205528 @default.
• W2564602076 hasConceptScore W2564602076C175444787 @default.
• W2564602076 hasConceptScore W2564602076C175551986 @default.
• W2564602076 hasConceptScore W2564602076C204827203 @default.
• W2564602076 hasConceptScore W2564602076C21922175 @default.
• W2564602076 hasConceptScore W2564602076C2776330181 @default.
• W2564602076 hasConceptScore W2564602076C31258907 @default.
• W2564602076 hasConceptScore W2564602076C33724603 @default.
• W2564602076 hasConceptScore W2564602076C41008148 @default.
• W2564602076 hasConceptScore W2564602076C49040817 @default.
• W2564602076 hasConceptScore W2564602076C49937458 @default.
• W2564602076 hasConceptScore W2564602076C6260449 @default.
• W2564602076 hasConceptScore W2564602076C76155785 @default.
• W2564602076 hasIssue "3" @default.
• W2564602076 hasLocation W25646020761 @default.
• W2564602076 hasLocation W25646020762 @default.
• W2564602076 hasLocation W25646020763 @default.
• W2564602076 hasLocation W25646020764 @default.
• W2564602076 hasLocation W25646020765 @default.
• W2564602076 hasOpenAccess W2564602076 @default.
• W2564602076 hasPrimaryLocation W25646020761 @default.
• W2564602076 hasRelatedWork W1973695542 @default.
• W2564602076 hasRelatedWork W1975116533 @default.
• W2564602076 hasRelatedWork W2058322665 @default.
• W2564602076 hasRelatedWork W2068138167 @default.
• W2564602076 hasRelatedWork W2141584761 @default.
• W2564602076 hasRelatedWork W2727263426 @default.
• W2564602076 hasRelatedWork W3013269438 @default.
• W2564602076 hasRelatedWork W3133461722 @default.
• W2564602076 hasRelatedWork W4232562375 @default.
• W2564602076 hasRelatedWork W4285805241 @default.
• W2564602076 hasVolume "25" @default.

• next