Optimization for the Design Matrix Realization Value With the Aim to Investigate Technological Processes

Koshevoy, N. D.; Gordienko, V. A.; Sukhobrus, Ye.A.

doi:10.1615/telecomradeng.v73.i15.60

Cited by 6 publications

(8 citation statements)

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“…Calculation of the value of the criterion of optimality of each permutation from the initial population of FA. This procedure is carried out using an improved genetic algorithm developed by the authors in the work [22].…”

Section: An Algorithm For Implementing the Methods Of Find Ing Soluti...mentioning

confidence: 99%

“…The work [22] indicated that the most popular evolutionary bio-inspired algorithms are the so-called «swarm» procedures (Particle Swarm Optimization -PSO). Among them, there are optimization algorithms based on cat swarms (Cat Swarm Optimization -CSO), which are very promising both from the point of view of speed and ease of implementation.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…At the same time, the researches [22,23] are not without some shortcomings that worsen the properties of the global extremum search process.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…An analysis of works [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] showed that the common shortcomings of the above mentioned researches are:…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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The development of solution search method using improved jumping frog algorithm

Mamoori,

Sova,

Zhuk

et al. 2023

EEJET

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The object of research is the decision making support systems. The subject of the research is the decision making process in management tasks using an advanced jumping frog algorithm (JFA), an advanced genetic algorithm and evolving artificial neural networks. A method of finding solutions with the use of improved JFA is proposed. The research is based on the JFA to find a solution regarding the object state. Evolving artificial neural networks are used to train frog agents (FA). The method has the following sequence of actions: – an input of initial data; – processing of initial data taking into account the degree of uncertainty; – calculation of the value of the criterion of optimality of each permutation from the initial FA population – global search of FA; – an improvement of the FA position in the search space; – a regulation of the speed of vehicle movement. – an improvement of the working conditions of JFA; – the FA rearrangement; – an unification of all memplexes into one group; – the verification of the fulfillment of the conditions of JFA operation; – the search for the best FA; – training of the FA knowledge bases. The originality of the proposed method consists in the arrangement of the FA taking into account the uncertainty of the initial data, the improved procedures of global and local edge taking into account the degree of data noise about the analysis object state, the adjustment of the degree of data noise during the FA movement, the adjustment of the speed of the FA movement. Also, the peculiarity of the proposed method is the use of an improved procedure for FA training. The use of the method makes it possible to increase the efficiency of data processing at the level of 14–18 % due to the use of additional improved procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes in the interests of solving national security problems

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Section: An Algorithm For Implementing the Methods Of Find Ing Soluti...mentioning

confidence: 99%

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…At the same time, the researches [22,23] are not without some shortcomings that worsen the properties of the global extremum search process.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…An analysis of works [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] showed that the common shortcomings of the above mentioned researches are:…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

See 2 more Smart Citations

The development of solution search method using improved jumping frog algorithm

Mamoori,

Sova,

Zhuk

et al. 2023

EEJET

View full text Add to dashboard Cite

show abstract

“…To design a multidimensional metamodel, an array of the training sample was created by calculating the ECD distribution with functional dependencies (11), (12) in the general case. Computer methods to uniformly fill the search hyperspace with reference points, that is the optimal designs of computational experiments (DOEs) [22], were used to form such an array. The use of DOEs with topology uncertainty of the hypersurface increases the probability of the reference points falling into the areas of extremes and kinds.…”

Section: Computer Design Of the Experiment Metamodel Designmentioning

confidence: 99%

Metrology and Measurement Systems

Halchenko¹,

Tychkov²,

Гальченко³

et al. 2021

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A mathematical method for nonlinear surrogate synthesis of frame surface eddy current probes providing a uniform eddy current density distribution in the testing object area is proposed. A metamodel of a frame movable eddy-current probe with a planar excitation system structure, used in the algorithm for surrogate optimal synthesis was created. The examples of a nonlinear synthesis of excitation systems with the application of the modern metaheuristic stochastic algorithms for finding the global extremum are considered. The numerical findings of the problem analyses are presented. The efficiency of the synthesized excitation structures was demonstrated on the basis of the eddy current density distribution graphs on the surface of the control zone of the object in comparison with classical analogues.

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