2019
DOI: 10.3103/s1068364x19020091
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Neural-Network Model for Predicting the Yield of Coking Products

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Cited by 3 publications
(3 citation statements)
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“…One of the problems of using evolutionary computations to optimize multiextremal functions is to get into a local extremum. To solve this problem, it is possible to use hybrid genetic algorithms [11][12][13]. The idea of hybrid algorithms is to combine a genetic algorithm with some other classical search method suitable for solving this problem.…”
Section: Application Of Heuristic Methods Of Finding the Optimal Consmentioning
confidence: 99%
“…One of the problems of using evolutionary computations to optimize multiextremal functions is to get into a local extremum. To solve this problem, it is possible to use hybrid genetic algorithms [11][12][13]. The idea of hybrid algorithms is to combine a genetic algorithm with some other classical search method suitable for solving this problem.…”
Section: Application Of Heuristic Methods Of Finding the Optimal Consmentioning
confidence: 99%
“…To design the cost-effective flexible road pavements, it is proposed to use a genetic algorithm. Genetic algorithm is based on an evolutionary search method that can be flexibly configured [9][10][11][12][13][14][15]. To carry out a computational experiment, 100 runs of each genetic algorithm modification were considered [1].…”
Section: Th International Innovative Mining Symposiummentioning
confidence: 99%
“…The advantage of genetic algorithms is the possibility to combine them with other optimization methods. A common approach is the inclusion of nonlinear programming methods into genetic algorithm for local optimization of chromosomes [1,[9][10][11][12][13][14][15].…”
Section: Th International Innovative Mining Symposiummentioning
confidence: 99%