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This article is cited in 5 scientific papers (total in 5 papers)
Cooperation of bio-inspired and evolutionary algorithms for neural network design
Shakhnaz A. Akhmedova, Vladimir V. Stanovov, Eugene S. Semenkin Reshetnev Siberian State University of Science and Technology,
Krasnoyarskiy Rabochiy, 31, Krasnoyarsk, 660037,
Russia
Abstract:
A meta-heuristic called Co-Operation of Biology-Related Algorithms (COBRA) with a fuzzy controller, as well as a new algorithm based on the cooperation of Differential Evolution and Particle Swarm Optimization (DE+PSO) and developed for solving real-valued optimization problems, were applied to the design of artificial neural networks. The usefulness and workability of both meta-heuristic approaches were demonstrated on various benchmarks. The neural network's weight coefficients represented as a string of real-valued variables are adjusted with the fuzzy controlled COBRA or with DE+PSO. Two classification problems (image and speech recognition problems) were solved with these approaches. Experiments showed that both cooperative optimization techniques demonstrate high performance and reliability in spite of the complexity of the solved optimization problems. The workability and usefulness of the proposed meta-heuristic optimization algorithms are confirmed.
Keywords:
co-operation, bio-inspired algorithms, differential evolution, neural networks, classification.
Received: 30.06.2017 Received in revised form: 12.09.2017 Accepted: 20.01.2018
Citation:
Shakhnaz A. Akhmedova, Vladimir V. Stanovov, Eugene S. Semenkin, “Cooperation of bio-inspired and evolutionary algorithms for neural network design”, J. Sib. Fed. Univ. Math. Phys., 11:2 (2018), 148–158
Linking options:
https://www.mathnet.ru/eng/jsfu648 https://www.mathnet.ru/eng/jsfu/v11/i2/p148
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