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Development of a solution search method using an improved locust swarm algorithm

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dc.contributor.authorOdarushchenko, O. B.
dc.contributor.authorОдарущенко, Олена Борисівна
dc.date.issued2023-10-30
dc.description.abstractThe object of the research is deci¬sion support systems. The subject of the research is the decision-mak¬ing process in management problems using the locust swarm algorithm and evolving artificial neural networks. A solution search method using an improved locust swarm algo¬rithm is proposed. The research is based on the locust swarm algorithm for finding a solution regarding the state of an object. For training locust agents (LA), evolving artificial neu¬ral networks are used. The method has the following sequence of steps: – input of initial data; – processing of initial data tak¬ing into account the degree of uncer¬tainty; – initial setting of LA in the search area; – determination of the initial speed of the LA movement; – a search vector is generated taking into account the degree of uncertainty; – calculation of the change in the value of the LA fitness function; – training of LA knowledge bases. The originality of the proposed method lies in the arrangement of LA taking into account the uncertainty of the initial data, improved proce¬dures of global and local search tak¬ing into account the degree of noise of data about the state of the analy¬sis object. Also, the originality of the research is avoiding the concentra¬tion of LA on the current best posi¬tions, reducing the probability of pre¬mature conv/ ergence of the algorithm and maintaining a balance between the convergence rate of the algorithm and diversification. The peculiarity of the proposed method is the use of an improved procedure for LA training. The training procedure consists in learning the parameters and archi¬tecture of individual elements and the architecture of the artificial neural network as a whole.
dc.identifier.citationDevelopment of a solution search method using an improved locust swarm algorithm / V. Tyurin et al. Eastern-European Journal of Enterprise Technologies. Vol. 5 No. 4 (125) (2023): Mathematics and Cybernetics - applied aspects. DOI: 10.15587/1729-4061.2023.287316
dc.identifier.otherUDC 004.81
dc.identifier.urihttps://dspace.pdau.edu.ua/handle/123456789/22178
dc.language.isoen
dc.publisherEastern-European Journal of Enterprise Technologies
dc.subjectswarm intelligence
dc.subjectdecision support systems
dc.subjecthierarchi¬cal systems
dc.subjectlocust swarm algorithm
dc.titleDevelopment of a solution search method using an improved locust swarm algorithm
dc.title.alternativeРозробка методу пошуку рішень з використанням удосконаленого алгоритму рою сарани
dc.typeArticle
dspace.entity.typePublication
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