Evolution strategies with q-Gaussian mutation for dynamic optimization problems (2010)
- Authors:
- Autor USP: TINÓS, RENATO - FFCLRP
- Unidade: FFCLRP
- Assunto: ROBÓTICA
- Language: Português
- Imprenta:
- Publisher: IEEE Computer Society
- Publisher place: São Bernardo do Campo
- Date published: 2010
- ISBN: 9780769542102
- Source:
- Título: Proceedings
- Conference titles: Joint Conference
-
ABNT
TINÓS, Renato e YANG, Shengxiang. Evolution strategies with q-Gaussian mutation for dynamic optimization problems. 2010, Anais.. São Bernardo do Campo: IEEE Computer Society, 2010. . Acesso em: 11 mar. 2026. -
APA
Tinós, R., & Yang, S. (2010). Evolution strategies with q-Gaussian mutation for dynamic optimization problems. In Proceedings. São Bernardo do Campo: IEEE Computer Society. -
NLM
Tinós R, Yang S. Evolution strategies with q-Gaussian mutation for dynamic optimization problems. Proceedings. 2010 ;[citado 2026 mar. 11 ] -
Vancouver
Tinós R, Yang S. Evolution strategies with q-Gaussian mutation for dynamic optimization problems. Proceedings. 2010 ;[citado 2026 mar. 11 ] - Programação evolutiva com distribuição de mutações auto-adaptativa aplicada a redes neurais artificiais
- A new method for identification of recombining components in the generalized partition crossover
- Quasi-optimal recombination operator
- Artificial neural network based crossover for evolutionary algorithms
- Analyzing evolutionary algorithms for dynamic optimization problems based on the dynamical systems approach
- Use of self-organizing suppression and q-Gaussian mutation in artificial immune systems
- Diversity control in genetic algorithms for protein structure prediction
- An efficient implementation of iterative partial transcription for the traveling salesman problem
- Analysing fitness landscape changes in evolutionary robots
- Improving an exact solver for the Traveling Salesman Problem using partition crossover
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