Modeling of the process of territorial communities formation using swarm intelligence algorithms

Lytvyn, Vasyl; Uhryn, Dmytro; Nadiein, Nazarii; Кlichuk, Oleg

doi:10.15587/2312-8372.2017.112198

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…In terms of complexity, algorithms can be simple (the iteration contains one process) and complex (the iteration contains several processes). Table 1 gives a generalized description of parameters of existing 𝑆𝐼𝑀 [8][9][10][11][12][13][14]. These parameters' values enable us to choose the method of swarm intelligence depending on the problem class.…”

Section: Methodsmentioning

confidence: 99%

“…Article [8] proposes an approach to the formation of territorial communities using algorithms of collective intelligence. The approved methodology for the formation of communities is investigated, and a mathematical model.…”

Section: Related Workmentioning

confidence: 99%

“…Step 4. For each task 𝑊 𝑖 , additional initial information is defined according to the conceptual model (8).…”

Section: Mgd S Mgd Amentioning

confidence: 99%

See 2 more Smart Citations

Information Technologies for Decision Support in Industry-Specific Geographic Information Systems based on Swarm Intelligence

Lytvyn¹,

Lozynska²,

Uhryn³

et al. 2023

IJMECS

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A method of choosing swarm optimization algorithms and using swarm intelligence for solving a certain class of optimization tasks in industry-specific geographic information systems was developed considering the stationarity characteristic of such systems. The method consists of 8 stages. Classes of swarm algorithms were studied. It is shown which classes of swarm algorithms should be used depending on the stationarity, quasi-stationarity or dynamics of the task solved by an industry geographic information system. An information model of geodata that consists in a formalized combination of their spatial and attributive components, which allows considering the relational, semantic and frame models of knowledge representation of the attributive component, was developed. A method of choosing optimization methods designed to work as part of a decision support system within an industry-specific geographic information system was developed. It includes conceptual information modeling, optimization criteria selection, and objective function analysis and modeling. This method allows choosing the most suitable swarm optimization method (or a set of methods).

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Information Technologies for Decision Support in Industry-Specific Geographic Information Systems based on Swarm Intelligence

Lytvyn¹,

Lozynska²,

Uhryn³

et al. 2023

IJMECS

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The Method of Clustering Geoinformation Data for Stationary Sectoral Geoinformation Systems Using Swarm Intelligence Methods

Lytvyn

Uhryn

Ushenko

et al. 2023

Lecture Notes in Networks and Systems

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Modeling of the process of territorial communities formation using swarm intelligence algorithms

Abstract: InformatIon and Control SyStemS: InformatIon teChnologIeS 17Technology audiT and producTion reserves -№ 5/2(37), 2017, © Lytvyn V., Uhryn D., Nadiein N., Klichuk O.

Cited by 2 publications

References 11 publications

Information Technologies for Decision Support in Industry-Specific Geographic Information Systems based on Swarm Intelligence

Information Technologies for Decision Support in Industry-Specific Geographic Information Systems based on Swarm Intelligence

The Method of Clustering Geoinformation Data for Stationary Sectoral Geoinformation Systems Using Swarm Intelligence Methods

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