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dc.date.accessioned2022-05-23T15:10:28Z
dc.date.available2022-05-23T15:10:28Z
dc.date.issued2022-03-09
dc.identifierdoi:10.17170/kobra-202205176191
dc.identifier.urihttp://hdl.handle.net/123456789/13852
dc.description.sponsorshipGefördert durch den Publikationsfonds der Universität Kasselger
dc.language.isoengeng
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectfour-bar mechanismeng
dc.subjectgoal attainment methodeng
dc.subjecthybrid genetic algorithmeng
dc.subjectmulti-objective optimizationeng
dc.subjectnon-dominated sorting genetic algorithm (NSGA-II)eng
dc.subjectquasi-Newton optimization methodeng
dc.subjectweed controleng
dc.subjectweed cultivatoreng
dc.subject.ddc620
dc.subject.ddc630
dc.titleMulti-Objective Optimal Design and Development of a Four-Bar Mechanism for Weed Controleng
dc.typeAufsatzeng
dcterms.abstractWeeds compete with crops for water, nutrients, and light consequently, have adverse effects on the crop yield and overall productivity. Mechanical weeding is the most common non-chemical method for weed control, which is applied in organic farming, and the weed cultivator is the most common implement in mechanical weeding. This study aimed to design and develop an innovative active tool to optimize the cultivation depth, which can avoid damage to crop roots and improve the key performance indicators of an inter-row cultivator. A quasi-Newton optimization method and a hybrid of the non-dominated sorting genetic algorithm (NSGA-II) and goal attainment method were separately applied to synthesize and develop a four-bar mechanism for weeding requirements. The transmission angle of the mechanism and the desired path of the weeding blade were simultaneously optimized using these multi-objective optimization techniques. The performance of the developed four-bar cultivator based on the optimization techniques was compared with the ones developed based on the classic methods and also with several conventional tools evaluated in other studies. The results showed that applying the quasi-Newton optimization method and hybrid genetic algorithm can propose a more effective weed cultivator in terms of performance indicators, namely weeding performance, mechanical damage to crop plants and cultivation depth. In addition, the optimization of the transmission angle guaranteed the smooth rotations in the mechanism’s joints.eng
dcterms.accessRightsopen access
dcterms.creatorHosseini, Hooman
dcterms.creatorFarzad, Abdulali
dcterms.creatorMajeed, Faizan
dcterms.creatorHensel, Oliver
dcterms.creatorNasirahmadi, Abozar
dc.relation.doidoi:10.3390/machines10030198
dc.subject.swdMechanische Unkrautbekämpfungger
dc.subject.swdOptimierungger
dc.subject.swdGenetischer Algorithmusger
dc.subject.swdMehrkriterielle Optimierungger
dc.type.versionpublishedVersioneng
dcterms.source.identifiereissn:2075-1702
dcterms.source.issueIssue 3
dcterms.source.journalMachineseng
dcterms.source.volumeVolume 10
kup.iskupfalseeng
dcterms.source.articlenumber198


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