The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform
Roberto Limao - One of the best experts on this subject based on the ideXlab platform.
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a fuzzy inference system inspired influence Function for the cultural algorithm with evolutionary programming applied to Real Valued Function optimization
Genetic and Evolutionary Computation Conference, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.
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GECCO - A fuzzy inference system-inspired influence Function for the cultural algorithm with evolutionary programming applied to Real-Valued Function optimization
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.
Michael Oneill - One of the best experts on this subject based on the ideXlab platform.
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social grammatical evolution with imitation learning for Real Valued Function estimation
Congress on Evolutionary Computation, 2017Co-Authors: Michael Oneill, David Fagan, Anthony BrabazonAbstract:Drawing on a rich literature concerning social learning in animals, this paper presents a variation of Grammatical Evolution (GE) which incorporates one of the most powerful forms of social learning, namely imitation learning. This replaces the traditional method of ‘communication’ between individuals in GE - crossover - which is drawn from an evolutionary metaphor. The paper provides an introduction to social learning, describes the proposed variant of GE, and tests on a series of benchmark symbolic regression problems. The results obtained are encouraging, being very competitive when compared with canonical GE. It is noted that the literature on social learning provides a number of useful meta-frameworks which can be used in the design of new search algorithms and to allow us to better understand the strengths and weaknesses of existing algorithms. Future work is indicated in this area.
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semantic similarity based crossover in gp the case for Real Valued Function regression
EA'09 Proceedings of the 9th international conference on Artificial evolution, 2009Co-Authors: Nguyen Quang Uy, Michael Oneill, Nguyen Xuan Hoai, Bob Mckay, Edgar GalvanlopezAbstract:In this paper we propose a new method for implementing the cross-over operator in Genetic Programming (GP) called Semantic Similarity based Crossover (SSC). This new operator is inspired by Semantic Aware Crossover (SAC) [20]. SSC extends SAC by adding semantics to control the change of the semantics of the individuals during the evolutionary process. The new crossover operator is then tested on a family of symbolic regression problems and compared with SAC as well as Standard Crossover (SC). The results from the experiments show that the change of the semantics (fitness) in the new SSC is smoother compared to SAC and SC. This leads to performance improvement in terms of percentage of successful runs and mean best fitness.
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semantic aware crossover for genetic programming the case for Real Valued Function regression
European Conference on Genetic Programming, 2009Co-Authors: Quang Uy Nguyen, Xuan Hoai Nguyen, Michael OneillAbstract:In this paper, we apply the ideas from [2] to investigate the effect of some semantic based guidance to the crossover operator of GP. We conduct a series of experiments on a family of Real-Valued symbolic regression problems, examining four different semantic aware crossover operators. One operator considers the semantics of the exchanged subtrees, while the other compares the semantics of the child trees to their parents. Two control operators are adopted which reverse the logic of the semantic equivalence test. The results show that on the family of test problems examined, the (approximate) semantic aware crossover operators can provide performance advantages over the standard subtree crossover adopted in Genetic Programming.
Huseyin Cakalli - One of the best experts on this subject based on the ideXlab platform.
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On downward half Cauchy sequences
Electronic Notes in Discrete Mathematics, 2018Co-Authors: Huseyin CakalliAbstract:Abstract In this paper, we introduce and investigate the concepts of down continuity and down compactness. A Real Valued Function f on a subset E of R, the set of Real numbers is down continuous if it preserves downward half Cauchy sequences. It turns out that the set of down continuous Functions is a proper subset of the set of continuous Functions.
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Strongly lacunary delta ward continuity
2015Co-Authors: Huseyin Cakalli, Huseyin KaplanAbstract:In this paper, the concepts of a lacunary statistically δ-quasi-Cauchy sequence and a strongly lacunary δ-quasi-Cauchy sequence are introduced, and investigated. In this investigation, we proved interesting theorems related to some newly defined continuities here, mainly, lacunary statistically δ-ward continuity, and strongly lacunary δ-ward continuity. A Real Valued Function f defined on a subset A of R, the set of Real numbers, is called lacunary statistically delta ward continuous on A if it preserves lacunary statistically delta quasi-Cauchy sequences of points in A, i.e. (f (αk)) is a lacunary statistically quasi-Cauchy sequence whenever (αk) is a lacunary statistically quasi-Cauchy sequences of points in A, and a Real Valued Function f defined on a subset A of R is called strongly lacunary delta ward continuous on A if it preserves strongly lacunary delta quasi-Cauchy sequences of points in A, i.e. (f (αk)) is a strongly lacunary quasi-Cauchy sequence whenever (αk) is a strongly lacunary quasi-Cauch...
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$\lambda$-statistically quasi-Cauchy sequences
arXiv: General Mathematics, 2013Co-Authors: Huseyin Cakalli, Ayse Sonmez, Cigdem Gunduz ArasAbstract:The main object of this paper is to investigate $\lambda$-statistically quasi-Cauchy sequences. A Real Valued Function $f$ defined on a subset $E$ of $\textbf{R}$, the set of Real numbers, is called $\lambda$-statistically ward continuous on $E$ if it preserves $\lambda$-statistically quasi-Cauchy sequences of points in $E$. It turns out that uniform continuity coincides with $\lambda$-statistically ward continuity on $\lambda$-statistically ward compact subsets.
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Strongly Cesaro type quasi-Cauchy sequences
arXiv: Functional Analysis, 2011Co-Authors: Huseyin CakalliAbstract:In this paper we call a Real-Valued Function $N_{\theta}$-ward continuous if it preserves $N_{\theta}$-quasi-Cauchy sequences where a sequence $\boldsymbol{\alpha}=(\alpha_{k})$ is defined to be $N_{\theta}$-quasi-Cauchy when the sequence $\Delta \boldsymbol{\alpha}$ is in $N^{0}_{\theta}$. We prove not only inclusion and compactness type theorems, but also continuity type theorems.
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On lacunary statistically quasi-Cauchy sequences
arXiv: Classical Analysis and ODEs, 2011Co-Authors: Huseyin Cakalli, Cigdem Gunduz Aras, Ayse SonmezAbstract:The main object of this paper is to investigate lacunary statistically ward continuity. We obtain some relations between this kind of continuity and some other kinds of continuities. It turns out that any lacunary statistically ward continuous Real Valued Function on a lacunary statistically ward compact subset $E\subset{\textbf{R}}$ is uniformly continuous.
Mario Augusto Da Costa Torres - One of the best experts on this subject based on the ideXlab platform.
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a fuzzy inference system inspired influence Function for the cultural algorithm with evolutionary programming applied to Real Valued Function optimization
Genetic and Evolutionary Computation Conference, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.
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GECCO - A fuzzy inference system-inspired influence Function for the cultural algorithm with evolutionary programming applied to Real-Valued Function optimization
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.
Otavio Noura Teixeira - One of the best experts on this subject based on the ideXlab platform.
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a fuzzy inference system inspired influence Function for the cultural algorithm with evolutionary programming applied to Real Valued Function optimization
Genetic and Evolutionary Computation Conference, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.
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GECCO - A fuzzy inference system-inspired influence Function for the cultural algorithm with evolutionary programming applied to Real-Valued Function optimization
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09, 2009Co-Authors: Mario Augusto Da Costa Torres, Rodrigo Magno Silva, Otavio Noura Teixeira, Roberto LimaoAbstract:In this paper, we present a Fuzzy Influence Function for the CAEP model (Cultural Algorithms with Evolutionary Programming) proposed by Chung [1] and extended by Zhu [6], applied to Real-Valued Function optimization. The proposal makes use of a Fuzzy Inference System 'FIS' to adjust an Influence Factor that represents the intensity of the influence of the Variation operator of the CAEP model. This paper also presents a comparative analysis of the proposed influence Function using a set of 17 of the CEC '05 benchmarking Functions.