Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308478532> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W4308478532 endingPage "513" @default.
- W4308478532 startingPage "502" @default.
- W4308478532 abstract "In any transport system, especially at industrial railway junctions, it is fundamentally important to build an effective timetable (traffic schedule) to regulate traffic flows. The task is complicated by the high dimensionality of the railway network of the node, the large number of variable parameters associated with scheduling the use of a traction resource (locomotives) during operation for sorting wagons and transporting payloads (ore, fuel, finished products and empty wagons). The problem is that most plotting problems are NP-hard, i.e. the algorithms for solving them, used to automate the process, may require an unacceptably long execution time by traditional methods of solving this problem (sequential, using reference information; method of thread laying). The article deals with the issues of building a mathematical model for dispatching an industrial railway junction to minimize the time of using locomotives in order to increase the efficiency of its operation. The mathematical model uses the technique of neuro-fuzzy computing to determine the parameters for identifying fuzzy systems and calculating the priorities of operations in the framework of creating a flexible schedule for the decision support system of the dispatching service. The results of modeling and recommendations on the use of the developed methodology are presented." @default.
- W4308478532 created "2022-11-12" @default.
- W4308478532 creator A5001960286 @default.
- W4308478532 creator A5015365092 @default.
- W4308478532 creator A5031865365 @default.
- W4308478532 creator A5071679567 @default.
- W4308478532 date "2023-02-01" @default.
- W4308478532 modified "2023-10-18" @default.
- W4308478532 title "Neuro-fuzzy-based mathematical model of dispatching of an industrial railway junction" @default.
- W4308478532 doi "https://doi.org/10.11591/eei.v12i1.4055" @default.
- W4308478532 hasPublicationYear "2023" @default.
- W4308478532 type Work @default.
- W4308478532 citedByCount "1" @default.
- W4308478532 countsByYear W43084785322023 @default.
- W4308478532 crossrefType "journal-article" @default.
- W4308478532 hasAuthorship W4308478532A5001960286 @default.
- W4308478532 hasAuthorship W4308478532A5015365092 @default.
- W4308478532 hasAuthorship W4308478532A5031865365 @default.
- W4308478532 hasAuthorship W4308478532A5071679567 @default.
- W4308478532 hasBestOaLocation W43084785321 @default.
- W4308478532 hasConcept C111919701 @default.
- W4308478532 hasConcept C127413603 @default.
- W4308478532 hasConcept C13736549 @default.
- W4308478532 hasConcept C154945302 @default.
- W4308478532 hasConcept C190839683 @default.
- W4308478532 hasConcept C205649164 @default.
- W4308478532 hasConcept C206729178 @default.
- W4308478532 hasConcept C21547014 @default.
- W4308478532 hasConcept C41008148 @default.
- W4308478532 hasConcept C42475967 @default.
- W4308478532 hasConcept C58166 @default.
- W4308478532 hasConcept C58640448 @default.
- W4308478532 hasConcept C68387754 @default.
- W4308478532 hasConcept C98045186 @default.
- W4308478532 hasConceptScore W4308478532C111919701 @default.
- W4308478532 hasConceptScore W4308478532C127413603 @default.
- W4308478532 hasConceptScore W4308478532C13736549 @default.
- W4308478532 hasConceptScore W4308478532C154945302 @default.
- W4308478532 hasConceptScore W4308478532C190839683 @default.
- W4308478532 hasConceptScore W4308478532C205649164 @default.
- W4308478532 hasConceptScore W4308478532C206729178 @default.
- W4308478532 hasConceptScore W4308478532C21547014 @default.
- W4308478532 hasConceptScore W4308478532C41008148 @default.
- W4308478532 hasConceptScore W4308478532C42475967 @default.
- W4308478532 hasConceptScore W4308478532C58166 @default.
- W4308478532 hasConceptScore W4308478532C58640448 @default.
- W4308478532 hasConceptScore W4308478532C68387754 @default.
- W4308478532 hasConceptScore W4308478532C98045186 @default.
- W4308478532 hasIssue "1" @default.
- W4308478532 hasLocation W43084785321 @default.
- W4308478532 hasLocation W43084785322 @default.
- W4308478532 hasOpenAccess W4308478532 @default.
- W4308478532 hasPrimaryLocation W43084785321 @default.
- W4308478532 hasRelatedWork W1895955244 @default.
- W4308478532 hasRelatedWork W1999534990 @default.
- W4308478532 hasRelatedWork W2017995910 @default.
- W4308478532 hasRelatedWork W207835341 @default.
- W4308478532 hasRelatedWork W2220836806 @default.
- W4308478532 hasRelatedWork W2504736554 @default.
- W4308478532 hasRelatedWork W2746047934 @default.
- W4308478532 hasRelatedWork W3166882358 @default.
- W4308478532 hasRelatedWork W3196268675 @default.
- W4308478532 hasRelatedWork W4313389879 @default.
- W4308478532 hasVolume "12" @default.
- W4308478532 isParatext "false" @default.
- W4308478532 isRetracted "false" @default.
- W4308478532 workType "article" @default.