• 25 Citations
20142019
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Personal profile

Research profile

Anil Yaman received his PhD degree in Mathematics and Computer Science in the Eindhoven University of Technology. He holds a B.S. degree from the Karadeniz Technical University (Turkey, 2010), and an M.S. degree from the City College of the City University of New York (USA, 2014). From 2013 to 2015, Anil held a research position at the Department of Biomedical Informatics in Columbia University; and from 2015 to 2016, he joined to INCAS³, an independent research institute founded in Assen, the Nederlands. His main areas of research include topics in computational intelligence, specifically naturally inspired algorithms specializing in evolutionary computation, artificial neural networks, and swarm intelligence. From 2015 to 2019, Anil involved in the H2020-FETOPEN project “PHOENIX: Exploring the Unknown through Reincarnation and Co-evolution”.

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  • 1 Similar Profiles
Evolutionary algorithms Engineering & Materials Science
Plasticity Engineering & Materials Science
Neurons Engineering & Materials Science
Evolutionary Algorithms Mathematics
Neural networks Engineering & Materials Science
Feedforward neural networks Engineering & Materials Science
Evolutionary Computation Mathematics
Chemical activation Engineering & Materials Science

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Research Output 2014 2019

  • 25 Citations
  • 8 Conference contribution
  • 5 Article
  • 1 Phd Thesis 1 (Research TU/e / Graduation TU/e)
2 Citations (Scopus)

A comparison of three differential evolution strategies in terms of early convergence with different population sizes

Yaman, A., Iacca, G. & Caraffini, F., 12 Feb 2019, Proceedings LeGO 2018, 14th International Global Optimization Workshop. Deutz, A. H., Hille, S. C., Sergeyev, Y. D. & Emmerich, M. T. M. (eds.). American Institute of Physics, 3 p. 20002. (AIP Conference Proceedings ; vol. 2070).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
fitness
optimization
1 Citation (Scopus)
30 Downloads (Pure)
Open Access
File
Feedforward neural networks
predictions
electronics
Carrier mobility
Aluminum

Evolution of biologically inspired learning in artificial neural networks

Yaman, A., 19 Nov 2019, Eindhoven: Technische Universiteit Eindhoven. 149 p.

Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

Open Access
File

Evolving plasticity for autonomous learning under changing environmental conditions

Yaman, A., Mocanu, D., Iacca, G., Coler, M., Fletcher, G. & Pechenizkiy, M., 2019, In : arXiv. 26 p., 1904.01709v1.

Research output: Contribution to journalArticleAcademic

Open Access
File
Plasticity
Neurons
Chemical activation
Reinforcement
Genetic algorithms

Improving (1+1) covariance matrix adaptation evolution strategy: a simple yet efficient approach

Caraffini, F., Iacca, G. & Yaman, A., 12 Feb 2019, Proceedings LeGO 2018 : 14th International Global Optimization Workshop. Deutz, A. H., Hille, S. C., Sergeyev, Y. D. & Emmerich, M. T. M. (eds.). Maryland: American Institute of Physics, 4 p. 20004. (AIP Conference Proceedings; vol. 2070).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
sampling
optimization
simplification

Press / Media

A bio-inspired approach to enhance learning in ANNs

Anil Yaman

4/04/19

1 item of Media coverage

Press/Media: Expert Comment