Collective Bionic Algorithm with Biogeography Based Migration Operator for Binary Optimization

Semenkin, ‪Eugene; Akhmedova, Shakhnaz; Семенкин, Евгений С.

doi:10.17516/1997-1397-2016-9-1-3-10

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…Experiments show that the modification of COBRA-b with a BBO migration operator allows better solutions to be found with a smaller number of calculations (Akhmedova and Semenkin, 2016). The results obtained in (Akhmedova and Semenkin, 2016) demonstrate that the new version of the algorithm outperforms the original COBRA-b both by the average number of function evaluations and by the best function value achieved during the work of the algorithm, averaged over 100 program runs.…”

Section: Co-operation Of Biology Related Algorithms (Cobra)mentioning

confidence: 94%

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Fuzzy Rule-based Classifier Design with Co-Operative Bionic Algorithm for Opinion Mining Problems

Akhmedova

Semenkin

Stanovov

2016

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

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Automatically generated fuzzy rule-based classifiers for opinion mining are presented in this paper. A collective nature-inspired self-tuning meta-heuristic for solving unconstrained real-valued optimization problems called CoOperation of Biology Related Algorithms and its modification with a biogeography migration operator for binary-parameter optimization problems were used for the design of classifiers. The basic idea consists in the representation of a fuzzy classifier rule base as a binary string and the parameters of the membership functions of the fuzzy classifier as a string of real-valued variables. Three opinion mining problems from the DEFT'07 competition were solved using the proposed classifiers. Experiments showed that the fuzzy classifiers developed in this way outperform many alternative methods at the given problems. The workability and usefulness of the proposed algorithm are confirmed.

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Section: Co-operation Of Biology Related Algorithms (Cobra)mentioning

confidence: 94%

“…As a consequence COBRA-b was also modified, specifically its migration operator (Akhmedova and Semenkin, 2016). For this purpose a biogeographybased optimization (BBO) (Simon, 2008) algorithm, which translates the natural distribution of species into a general problem solution, was used.…”

Section: Co-operation Of Biology Related Algorithms (Cobra)mentioning

confidence: 99%

Fuzzy Rule-based Classifier Design with Co-Operative Bionic Algorithm for Opinion Mining Problems

Akhmedova

Semenkin

Stanovov

2016

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

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“…Genetic algorithms (GAs) are among the most demanded evolutionary search techniques [24]. Due to their intrinsic parallelism, these algorithms make it possible to find a set of Pareto-optimal solutions in a single algorithm run [25].…”

Section: Introductionmentioning

confidence: 99%

Development of an Algorithm for Multicriteria Optimization of Deep Learning Neural Networks

Alexandrov

Kirichek²,

Kuklin

et al. 2023

HighTech. Innov. J.

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Nowadays, machine learning methods are actively used to process big data. A promising direction is neural networks, in which structure optimization occurs on the principles of self-configuration. Genetic algorithms are applied to solve this nontrivial problem. Most multicriteria evolutionary algorithms use a procedure known as non-dominant sorting to rank decisions. However, the efficiency of procedures for adding points and updating rank values in non-dominated sorting (incremental non-dominated sorting) remains low. In this regard, this research improves the performance of these algorithms, including the condition of an asynchronous calculation of the fitness of individuals. The relevance of the research is determined by the fact that although many scholars and specialists have studied the self-tuning of neural networks, they have not yet proposed a comprehensive solution to this problem. In particular, algorithms for efficient non-dominated sorting under conditions of incremental and asynchronous updates when using evolutionary methods of multicriteria optimization have not been fully developed to date. To achieve this goal, a hybrid co-evolutionary algorithm was developed that significantly outperforms all algorithms included in it, including error-back propagation and genetic algorithms that operate separately. The novelty of the obtained results lies in the fact that the developed algorithms have minimal asymptotic complexity. The practical value of the developed algorithms is associated with the fact that they make it possible to solve applied problems of increased complexity in a practically acceptable time. Doi: 10.28991/HIJ-2023-04-01-011 Full Text: PDF

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Collective Bionic Algorithm with Biogeography Based Migration Operator for Binary Optimization

Cited by 2 publications

References 12 publications

Fuzzy Rule-based Classifier Design with Co-Operative Bionic Algorithm for Opinion Mining Problems

Fuzzy Rule-based Classifier Design with Co-Operative Bionic Algorithm for Opinion Mining Problems

Development of an Algorithm for Multicriteria Optimization of Deep Learning Neural Networks

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