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Filtros : "Grã-Bretanha (Reino Unido, UK)" "FFCLRP-595" Removido: "Reino Unido" Limpar

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1 - 12 (12 records)

  • Artigo de periodico

    Clustered and deep echo state networks for signal noise reduction (2022)

    Oliveira Junior, Laercio de; Stelzer, Florian; Liang, Zhao

    Source: Machine Learning. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, SISTEMAS DINÂMICOS

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      OLIVEIRA JUNIOR, Laercio de e STELZER, Florian e LIANG, Zhao. Clustered and deep echo state networks for signal noise reduction. Machine Learning, v. 111, n. 8, p. 2885-2904, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10994-022-06135-6. Acesso em: 24 ago. 2024.

    • APA

      Oliveira Junior, L. de, Stelzer, F., & Liang, Z. (2022). Clustered and deep echo state networks for signal noise reduction. Machine Learning, 111( 8), 2885-2904. doi:10.1007/s10994-022-06135-6

    • NLM

      Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/s10994-022-06135-6

    • Vancouver

      Oliveira Junior L de, Stelzer F, Liang Z. Clustered and deep echo state networks for signal noise reduction [Internet]. Machine Learning. 2022 ; 111( 8): 2885-2904.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/s10994-022-06135-6

  • Trabalho de evento-anais periodico

    Partition crossover for continuous optimization: ePX (2021)

    Tinós, Renato ; Whitley, Darrell; Chicano, Francisco; Ochoa, Gabriela

    Source: Proceedings GECCO '21. Conference titles: Genetic and Evolutionary Computation Conference - GECCO '21. Unidade: FFCLRP

    Subjects: OTIMIZAÇÃO COMBINATÓRIA, TEORIA DA COMPUTAÇÃO, OPERADORES

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      TINÓS, Renato et al. Partition crossover for continuous optimization: ePX. Proceedings GECCO '21. New York: ACM. Disponível em: https://doi.org/10.1145/3449639.3459296. Acesso em: 24 ago. 2024. , 2021

    • APA

      Tinós, R., Whitley, D., Chicano, F., & Ochoa, G. (2021). Partition crossover for continuous optimization: ePX. Proceedings GECCO '21. New York: ACM. doi:10.1145/3449639.3459296

    • NLM

      Tinós R, Whitley D, Chicano F, Ochoa G. Partition crossover for continuous optimization: ePX [Internet]. Proceedings GECCO '21. 2021 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3449639.3459296

    • Vancouver

      Tinós R, Whitley D, Chicano F, Ochoa G. Partition crossover for continuous optimization: ePX [Internet]. Proceedings GECCO '21. 2021 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3449639.3459296

  • Artigo de periodico

    A new generalized partition crossover for the traveling salesman problem: tunneling between local optima (2020)

    Tinós, Renato ; Whitley, Darrell; Ochoa, Gabriela

    Source: Evolutionary Computation. Unidade: FFCLRP

    Subjects: COMPUTAÇÃO EVOLUTIVA, OTIMIZAÇÃO COMBINATÓRIA

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      TINÓS, Renato e WHITLEY, Darrell e OCHOA, Gabriela. A new generalized partition crossover for the traveling salesman problem: tunneling between local optima. Evolutionary Computation, v. 28, n. 2, p. 255-288, 2020Tradução . . Disponível em: https://doi.org/10.1162/evco_a_00254. Acesso em: 24 ago. 2024.

    • APA

      Tinós, R., Whitley, D., & Ochoa, G. (2020). A new generalized partition crossover for the traveling salesman problem: tunneling between local optima. Evolutionary Computation, 28( 2), 255-288. doi:10.1162/evco_a_00254

    • NLM

      Tinós R, Whitley D, Ochoa G. A new generalized partition crossover for the traveling salesman problem: tunneling between local optima [Internet]. Evolutionary Computation. 2020 ; 28( 2): 255-288.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1162/evco_a_00254

    • Vancouver

      Tinós R, Whitley D, Ochoa G. A new generalized partition crossover for the traveling salesman problem: tunneling between local optima [Internet]. Evolutionary Computation. 2020 ; 28( 2): 255-288.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1162/evco_a_00254

  • Artigo de periodico

    A framework for inducing artificial changes in optimization problems (2019)

    Tinós, Renato ; Yang, Shengxiang

    Source: Information Sciences. Unidade: FFCLRP

    Subjects: ALGORITMOS, OTIMIZAÇÃO COMBINATÓRIA

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      TINÓS, Renato e YANG, Shengxiang. A framework for inducing artificial changes in optimization problems. Information Sciences, v. 485, p. 486-504, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2019.02.027. Acesso em: 24 ago. 2024.

    • APA

      Tinós, R., & Yang, S. (2019). A framework for inducing artificial changes in optimization problems. Information Sciences, 485, 486-504. doi:10.1016/j.ins.2019.02.027

    • NLM

      Tinós R, Yang S. A framework for inducing artificial changes in optimization problems [Internet]. Information Sciences. 2019 ; 485 486-504.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1016/j.ins.2019.02.027

    • Vancouver

      Tinós R, Yang S. A framework for inducing artificial changes in optimization problems [Internet]. Information Sciences. 2019 ; 485 486-504.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1016/j.ins.2019.02.027

  • Trabalho de evento-anais periodico

    Quasi-optimal recombination operator (2019)

    Chicano, Francisco ; Ochoa, Gabriela ; Whitley, Darrell; Tinós, Renato

    Source: Lecture Notes in Computer Science. Conference titles: European Conference on Evolutionary Computation in Combinatorial Optimization - EvoCOP. Unidade: FFCLRP

    Subjects: OPERADORES, CIÊNCIA DA COMPUTAÇÃO, OTIMIZAÇÃO COMBINATÓRIA

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      CHICANO, Francisco et al. Quasi-optimal recombination operator. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-16711-0_9. Acesso em: 24 ago. 2024. , 2019

    • APA

      Chicano, F., Ochoa, G., Whitley, D., & Tinós, R. (2019). Quasi-optimal recombination operator. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-16711-0_9

    • NLM

      Chicano F, Ochoa G, Whitley D, Tinós R. Quasi-optimal recombination operator [Internet]. Lecture Notes in Computer Science. 2019 ; 11452 131-146.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/978-3-030-16711-0_9

    • Vancouver

      Chicano F, Ochoa G, Whitley D, Tinós R. Quasi-optimal recombination operator [Internet]. Lecture Notes in Computer Science. 2019 ; 11452 131-146.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/978-3-030-16711-0_9

  • Trabalho de evento-anais periodico

    Enhancing partition crossover with articulation points analysis (2018)

    Chicano, Francisco ; Ochoa, Gabriela ; Whitley, Darrell; Tinós, Renato

    Source: Proceedings GECCO '18. Conference titles: The Genetic and Evolutionary Computation Conference (GECCO '18). Unidade: FFCLRP

    Subjects: OTIMIZAÇÃO COMBINATÓRIA, MATEMÁTICA DA COMPUTAÇÃO, CIÊNCIA DA COMPUTAÇÃO

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      CHICANO, Francisco et al. Enhancing partition crossover with articulation points analysis. Proceedings GECCO '18. New York: ACM. Disponível em: https://riuma.uma.es/xmlui/bitstream/handle/10630/16353/pxap-gecco2018-riuma.pdf?sequence=1&isAllowed=y. Acesso em: 24 ago. 2024. , 2018

    • APA

      Chicano, F., Ochoa, G., Whitley, D., & Tinós, R. (2018). Enhancing partition crossover with articulation points analysis. Proceedings GECCO '18. New York: ACM. Recuperado de https://riuma.uma.es/xmlui/bitstream/handle/10630/16353/pxap-gecco2018-riuma.pdf?sequence=1&isAllowed=y

    • NLM

      Chicano F, Ochoa G, Whitley D, Tinós R. Enhancing partition crossover with articulation points analysis [Internet]. Proceedings GECCO '18. 2018 ;[citado 2024 ago. 24 ] Available from: https://riuma.uma.es/xmlui/bitstream/handle/10630/16353/pxap-gecco2018-riuma.pdf?sequence=1&isAllowed=y

    • Vancouver

      Chicano F, Ochoa G, Whitley D, Tinós R. Enhancing partition crossover with articulation points analysis [Internet]. Proceedings GECCO '18. 2018 ;[citado 2024 ago. 24 ] Available from: https://riuma.uma.es/xmlui/bitstream/handle/10630/16353/pxap-gecco2018-riuma.pdf?sequence=1&isAllowed=y

  • Artigo de periodico

    Multi-objective genetic algorithms in the study of the genetic code’s adaptability (2018)

    Oliveira, Lariza Laura de; Freitas, Alex A.; Tinós, Renato

    Source: Information Sciences. Unidade: FFCLRP

    Subjects: CÓDIGO GENÉTICO, ALGORITMOS GENÉTICOS

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      OLIVEIRA, Lariza Laura de e FREITAS, Alex A. e TINÓS, Renato. Multi-objective genetic algorithms in the study of the genetic code’s adaptability. Information Sciences, v. 425, p. 48-61, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2017.10.022. Acesso em: 24 ago. 2024.

    • APA

      Oliveira, L. L. de, Freitas, A. A., & Tinós, R. (2018). Multi-objective genetic algorithms in the study of the genetic code’s adaptability. Information Sciences, 425, 48-61. doi:10.1016/j.ins.2017.10.022

    • NLM

      Oliveira LL de, Freitas AA, Tinós R. Multi-objective genetic algorithms in the study of the genetic code’s adaptability [Internet]. Information Sciences. 2018 ; 425 48-61.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1016/j.ins.2017.10.022

    • Vancouver

      Oliveira LL de, Freitas AA, Tinós R. Multi-objective genetic algorithms in the study of the genetic code’s adaptability [Internet]. Information Sciences. 2018 ; 425 48-61.[citado 2024 ago. 24 ] Available from: https://doi.org/10.1016/j.ins.2017.10.022

  • Trabalho de evento

    Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search (2017)

    Chicano, Francisco; Ochoa, Gabriela; Whitley, Darrell; Tinós, Renato

    Source: Proceedings. Conference titles: Genetic and Evolutionary Computation Conference (GECCO). Unidade: FFCLRP

    Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, HEURÍSTICA

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      CHICANO, Francisco et al. Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search. 2017, Anais.. Berlin: ACM, 2017. Disponível em: https://doi.org/10.1145/3071178.3071285. Acesso em: 24 ago. 2024.

    • APA

      Chicano, F., Ochoa, G., Whitley, D., & Tinós, R. (2017). Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search. In Proceedings. Berlin: ACM. doi:10.1145/3071178.3071285

    • NLM

      Chicano F, Ochoa G, Whitley D, Tinós R. Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search [Internet]. Proceedings. 2017 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3071178.3071285

    • Vancouver

      Chicano F, Ochoa G, Whitley D, Tinós R. Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search [Internet]. Proceedings. 2017 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1145/3071178.3071285

  • Trabalho de evento

    Nature-inspired graph optimization for dimensionality reduction (2017)

    Carneiro, Murillo G.; Cupertino, Thiago H.; Cheng, Ran; Jin, Yaochu; Liang, Zhao

    Source: Proceedings. Conference titles: International Conference on Tools with Artficial Intelligence. Unidade: FFCLRP

    Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL

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      CARNEIRO, Murillo G. et al. Nature-inspired graph optimization for dimensionality reduction. 2017, Anais.. Boston: IEEE, 2017. . Acesso em: 24 ago. 2024.

    • APA

      Carneiro, M. G., Cupertino, T. H., Cheng, R., Jin, Y., & Liang, Z. (2017). Nature-inspired graph optimization for dimensionality reduction. In Proceedings. Boston: IEEE.

    • NLM

      Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 ago. 24 ]

    • Vancouver

      Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 ago. 24 ]

  • Parte de monografia/livro

    Tunneling crossover networks for the asymmetric TSP (2016)

    Veerapen, Nadarajen; Ochoa, Gabriela; Tinós, Renato; Whitley, Darrell

    Source: Lecture Notes in Computer Science. v. 9921. Unidade: FFCLRP

    Subjects: INTELIGÊNCIA ARTIFICIAL, SOLUÇÃO DE PROBLEMAS

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      VEERAPEN, Nadarajen et al. Tunneling crossover networks for the asymmetric TSP. Lecture Notes in Computer Science. v. 9921. Tradução . Cham: Springer, 2016. . . Acesso em: 24 ago. 2024.

    • APA

      Veerapen, N., Ochoa, G., Tinós, R., & Whitley, D. (2016). Tunneling crossover networks for the asymmetric TSP. In Lecture Notes in Computer Science. v. 9921. Cham: Springer.

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      Veerapen N, Ochoa G, Tinós R, Whitley D. Tunneling crossover networks for the asymmetric TSP. In: Lecture Notes in Computer Science. v. 9921. Cham: Springer; 2016. [citado 2024 ago. 24 ]

    • Vancouver

      Veerapen N, Ochoa G, Tinós R, Whitley D. Tunneling crossover networks for the asymmetric TSP. In: Lecture Notes in Computer Science. v. 9921. Cham: Springer; 2016. [citado 2024 ago. 24 ]

  • Parte de monografia/livro

    Artificially inducing environmental changes in evolutionary dynamic optimization (2016)

    Tinós, Renato; Yang, Shengxiang

    Source: Lecture Notes in Computer Science. v. 9921. Unidade: FFCLRP

    Subjects: COMPUTAÇÃO EVOLUTIVA, MEIO AMBIENTE, MUDANÇA

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      TINÓS, Renato e YANG, Shengxiang. Artificially inducing environmental changes in evolutionary dynamic optimization. Lecture Notes in Computer Science. v. 9921. Tradução . Cham: Springer, 2016. . Disponível em: https://doi.org/10.1007/978-3-319-45823-6_21. Acesso em: 24 ago. 2024.

    • APA

      Tinós, R., & Yang, S. (2016). Artificially inducing environmental changes in evolutionary dynamic optimization. In Lecture Notes in Computer Science. v. 9921. Cham: Springer. doi:10.1007/978-3-319-45823-6_21

    • NLM

      Tinós R, Yang S. Artificially inducing environmental changes in evolutionary dynamic optimization [Internet]. In: Lecture Notes in Computer Science. v. 9921. Cham: Springer; 2016. [citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/978-3-319-45823-6_21

    • Vancouver

      Tinós R, Yang S. Artificially inducing environmental changes in evolutionary dynamic optimization [Internet]. In: Lecture Notes in Computer Science. v. 9921. Cham: Springer; 2016. [citado 2024 ago. 24 ] Available from: https://doi.org/10.1007/978-3-319-45823-6_21

  • Trabalho de evento

    Network structural optimization based on swarm intelligence for highlevel classification (2016)

    Carneiro, Murillo G.; Liang, Zhao; Ran, Cheng; Jin, Yaochu

    Source: Annals. Conference titles: IEEE World Congress on Computational Intelligence. Unidade: FFCLRP

    Subjects: INTELIGÊNCIA ARTIFICIAL, REDES COMPLEXAS

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      CARNEIRO, Murillo G. et al. Network structural optimization based on swarm intelligence for highlevel classification. 2016, Anais.. Vancouver: IEEE, 2016. Disponível em: https://doi.org/10.1109/IJCNN.2016.7727681. Acesso em: 24 ago. 2024.

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      Carneiro, M. G., Liang, Z., Ran, C., & Jin, Y. (2016). Network structural optimization based on swarm intelligence for highlevel classification. In Annals. Vancouver: IEEE. doi:10.1109/IJCNN.2016.7727681

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      Carneiro MG, Liang Z, Ran C, Jin Y. Network structural optimization based on swarm intelligence for highlevel classification [Internet]. Annals. 2016 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1109/IJCNN.2016.7727681

    • Vancouver

      Carneiro MG, Liang Z, Ran C, Jin Y. Network structural optimization based on swarm intelligence for highlevel classification [Internet]. Annals. 2016 ;[citado 2024 ago. 24 ] Available from: https://doi.org/10.1109/IJCNN.2016.7727681
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