Evolutionary programming with q-Gaussian mutation for dynamic optimization problems (2008)
- Authors:
- Autor USP: TINÓS, RENATO - FFCLRP
- Unidade: FFCLRP
- Assunto: ALGORITMOS
- Language: Inglês
- Imprenta:
- Source:
- Título: Program
- Conference titles: IEEE World Congress on Computational Intelligence
-
ABNT
TINÓS, Renato e YANG, Shengxiang. Evolutionary programming with q-Gaussian mutation for dynamic optimization problems. 2008, Anais.. Hong Kong: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 2008. . Acesso em: 18 mar. 2026. -
APA
Tinós, R., & Yang, S. (2008). Evolutionary programming with q-Gaussian mutation for dynamic optimization problems. In Program. Hong Kong: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. -
NLM
Tinós R, Yang S. Evolutionary programming with q-Gaussian mutation for dynamic optimization problems. Program. 2008 ;[citado 2026 mar. 18 ] -
Vancouver
Tinós R, Yang S. Evolutionary programming with q-Gaussian mutation for dynamic optimization problems. Program. 2008 ;[citado 2026 mar. 18 ] - 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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