Rodyti trumpą aprašą

dc.contributor.authorAndziulis, Arūnas
dc.contributor.authorEglynas, Tomas
dc.contributor.authorBogdevičius, Marijonas
dc.contributor.authorLenkauskas, Tomas
dc.contributor.authorJusis, Mindaugas
dc.date.accessioned2023-09-18T16:52:52Z
dc.date.available2023-09-18T16:52:52Z
dc.date.issued2016
dc.identifier.issn2304-9693
dc.identifier.other(BIS)VGT02-000032227
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/117578
dc.description.abstractOne of most important research area of our paper is development of adaptive container loading system w ith computer vision algorithms for smooth container lan ding on the platform (truck, trailer or well car of the train), whereas excessive vibration is caused at th at moment, this vibration and shocks can cause cont ainer and/or cargo damage. This paper presents container crane grabber adaptive positioning subsystem that uses computer vision algorithms. Designed subsystem consists of two separate parts: an automatic image recognition system and the adaptive control system, which is based on neural network with fuzzy interf ace. This network is using learning algorithms so it can easily control container crane motors and adapt to changing conditions (container weight, platform hei ght). Functional computer vision algorithms is prop osed and based on them computer programs was developed. Electric circuits is also created and described, th at allows testing and validation of this subsystem.eng
dc.format.extentp. 21-28
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:20309817/datastreams/MAIN/content
dc.subjectTD03 - Transporto sistemų ir eismo modeliavimas, optimizavimas, sauga ir valdymas / Transport systems and traffic modeling, optimization, safety and management
dc.titleDevelopment of an adaptive intermodal container handling control subsystem based on automatic recognition algorithms
dc.typeStraipsnis kitame recenzuotame leidinyje / Article in other peer-reviewed source
dcterms.licenseCreative Commons – Attribution – NonCommercial – 4.0 International
dcterms.references9
dc.type.pubtypeS4 - Straipsnis kitame recenzuotame leidinyje / Article in other peer-reviewed publication
dc.contributor.institutionKlaipėdos universitetas
dc.contributor.institutionVilniaus Gedimino technikos universitetas Klaipėdos universitetas
dc.contributor.facultyTransporto inžinerijos fakultetas / Faculty of Transport Engineering
dc.contributor.facultyDarbų ir civilinės saugos skyrius / Darbų ir civilinės saugos skyrius
dc.subject.researchfieldT 003 - Transporto inžinerija / Transport engineering
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enadaptive positioning
dc.subject.enneural network
dc.subject.encontrol system
dc.subject.enintermodal containers
dc.subject.enlearning algorithms
dcterms.sourcetitleEuropean International Journal of Science and Technology (EIJST)
dc.description.issueno. 3
dc.description.volumevol. 5
dc.publisher.nameCenter for Enhancing Knowledge
dc.publisher.cityNewcastel
dc.identifier.doi1
dc.identifier.elaba20309817


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