Výsledky vyhľadávania - Genetic algorithm parameter adaptation

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  1. 1

    A simultaneous parameter adaptation scheme for genetic algorithms with application to phased array synthesis Autor Boeringer, D.W., Werner, D.H., Machuga, D.W.

    ISSN: 0018-926X, 1558-2221
    Vydavateľské údaje: New York IEEE 01.01.2005
    “… An important issue facing the user is the selection of genetic algorithm parameters, such as mutation rate, mutation range, and number of crossovers…”
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    Parallel genetic algorithm with parameter adaptation Autor Tongchim, Shisanu, Chongstitvatana, Prabhas

    ISSN: 0020-0190, 1872-6119
    Vydavateľské údaje: Elsevier B.V 15.04.2002
    Vydané v Information processing letters (15.04.2002)
    “… The parameter adaptation occurs in parallel to the running of the genetic algorithm. The proposed method is compared with the algorithms that use random parameter sets and a standard parameter set…”
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  3. 3

    Maintaining Healthy Population Diversity Using Adaptive Crossover, Mutation, and Selection Autor McGinley, Brian, Maher, John, O'Riordan, Colm, Morgan, Fearghal

    ISSN: 1089-778X, 1941-0026
    Vydavateľské údaje: New York, NY IEEE 01.10.2011
    “…This paper presents ACROMUSE, a novel genetic algorithm (GA) which adapts crossover, mutation, and selection parameters…”
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  4. 4

    CSPA: Channel Selection and Parameter Adaptation scheme based on genetic algorithm for cognitive radio Ad Hoc networks Autor Aslam, Saleem, Lee, Kyung Geun

    ISSN: 1687-1499, 1687-1472, 1687-1499
    Vydavateľské údaje: Cham Springer International Publishing 21.11.2012
    “… CR has two distinct features, the spectrum sensing and the parameter adaptation. The former feature helps the CR to find the vacant spectrum slots/channels…”
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    Video segmentation using genetic algorithms with automatic parameter adaptation Autor Kim, E.Y.

    ISSN: 0013-5194, 1350-911X
    Vydavateľské údaje: London Institution of Electrical Engineers 25.11.2004
    Vydané v Electronics letters (25.11.2004)
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    Video segmentation using genetic algorithms with automatic parameter adaptation Autor Kim, E Y

    ISSN: 0013-5194, 1350-911X
    Vydavateľské údaje: Stevenage John Wiley & Sons, Inc 25.11.2004
    Vydané v Electronics letters (25.11.2004)
    “…A novel genetic algorithm for video sequence segmentation is presented. The novelty of the approach is that the mating rates such as crossover rate and mutation rate are not constant, but spatio-temporally varying…”
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  8. 8

    A novel approach in parameter adaptation and diversity maintenance for genetic algorithms Autor Lee, K.-H., Leung, K.-S., Ho, C.-W., Wong, Y.-Y.

    ISSN: 1432-7643, 1433-7479
    Vydavateľské údaje: Heidelberg Springer Nature B.V 01.08.2003
    Vydané v Soft computing (Berlin, Germany) (01.08.2003)
    “…In this paper, we propose a probabilistic rule-driven adaptive model (PRAM) for parameter adaptation and a repelling approach for diversity maintenance in genetic algorithms…”
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    Hybrid Genetic-Environmental Adaptation Algorithm to Improve Parameters of COCOMO for Software Cost Estimation Autor Gandomani, Taghi Javdani, Dashti, Maedeh, Nafchi, Mina Zaiei

    Vydavateľské údaje: IEEE 02.03.2022
    “…) and environmental adaptation (EA) methods. The results indicate that the EA algorithm can solve the divergence issue of the genetic algorithm and optimize the coefficients of the COCOMO model as well…”
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    Optimization of interconnects for signal integrity using self - adaptation in real - parameter genetic algorithms with simulated binary cross over (SBX) Autor Sabanayagam, A., Kumar, V.A., Raju, S., Kumar, N.S.

    ISBN: 8190357514, 9788190357517
    Vydavateľské údaje: IEEE 01.11.2008
    “…Signal integrity is the ability of a signal to generate correct responses in the circuit. High speed interconnect is the one in which the time taken by the…”
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    Operator and parameter adaptation in genetic algorithms Autor Smith, J. E., Fogarty, T. C.

    ISSN: 1432-7643, 1433-7479
    Vydavateľské údaje: Heidelberg Springer Nature B.V 01.06.1997
    Vydané v Soft computing (Berlin, Germany) (01.06.1997)
    “…Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection…”
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    A new parameter adaptation method for Genetic Algorithms and Ant Colony Optimization algorithms Autor Byerly, Adam, Uskov, Alexander

    ISSN: 2154-0373
    Vydavateľské údaje: IEEE 01.05.2016
    “… This paper introduces a genetic algorithm implementation, an ant colony optimization algorithm implementation, and a method of adapting the parameters for the algorithms during the course…”
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    Konferenčný príspevok.. Journal Article
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    The automatic design of parameter adaptation techniques for differential evolution with genetic programming Autor Stanovov, Vladimir, Akhmedova, Shakhnaz, Semenkin, Eugene

    ISSN: 0950-7051, 1872-7409
    Vydavateľské údaje: Amsterdam Elsevier B.V 05.03.2022
    Vydané v Knowledge-based systems (05.03.2022)
    “…This study proposes a technique aimed at the automatic search for parameter adaptation strategies in a differential evolution algorithm with genetic programming symbolic regression…”
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    Real-coded genetic algorithm parameter setting for cognitive radio adaptation Autor Saoucha, N. Ali, Lammari, A. C., Benatchba, K.

    Vydavateľské údaje: IEEE 01.06.2013
    “… Transmission parameters adaptation in a dynamic multicarrier environment has been previously studied using genetic algorithms (GA…”
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    Bayesian network as an adaptive parameter setting approach for genetic algorithms Autor Corriveau, Guillaume, Guilbault, Raynald, Tahan, Antoine, Sabourin, Robert

    ISSN: 2199-4536, 2198-6053
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2016
    Vydané v Complex & intelligent systems (01.03.2016)
    “…Parameter setting currently ranks among the most actively researched topics in the evolutionary algorithm (EA) community…”
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    Energy-efficient clustering in wireless sensor networks using multi-objective genetic algorithm with adaptive parameter Autor Ejaz, Muhammad, Asim, Muhammad, Jinsong, Gui, Chelloug, Samia Allaoua, El-Latif, Ahmed A. Abd

    ISSN: 1018-4864, 1572-9451
    Vydavateľské údaje: New York Springer Nature B.V 01.03.2026
    Vydané v Telecommunication systems (01.03.2026)
    “… We propose the Multi-Objective Genetic Algorithm with Adaptive Parameters (MOGAA), integrating four key components…”
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    Self adaptation of parameters for MCPC in genetic algorithms Autor Esquivel, S.C, Leiva, H.A, Gallard, R.H

    ISSN: 1666-6046, 1666-6038
    Vydavateľské údaje: La Plata Graduate Network of Argentine Universities with Computer Science Schools (RedUNCI) 01.03.2000
    “… Self-adaptation of parameters…”
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    2-Dimensional genetic algorithm exhibited an essentiality of gene interaction for evolution Autor Akashi, Motohiro, Fujihara, Ichiro, Takemura, Masaharu, Furusawa, Mitsuru

    ISSN: 0022-5193, 1095-8541, 1095-8541
    Vydavateľské údaje: England Elsevier Ltd 07.04.2022
    Vydané v Journal of theoretical biology (07.04.2022)
    “… In a previous study, the 2-dimensional genetic algorithm (2DGA) program, including a gene interaction parameter, could simulate punctuated equilibrium under the disparity mode…”
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    Incorporating domain-specific knowledge into a genetic algorithm to implement case-based reasoning adaptation Autor Passone, S., Chung, P.W.H., Nassehi, V.

    ISSN: 0950-7051, 1872-7409
    Vydavateľské údaje: Elsevier B.V 01.07.2006
    Vydané v Knowledge-based systems (01.07.2006)
    “… A new adaptation approach is presented in this paper which uses a modified genetic algorithm incorporating specific domain knowledge and information provided by the retrieved cases…”
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    Genetic algorithms with self-adaptation for predictive classification of Medicare standardized payments for physical therapists Autor Norat, Reamonn, Wu, Annie S., Liu, Xinliang

    ISSN: 0957-4174, 1873-6793
    Vydavateľské údaje: Elsevier Ltd 15.05.2023
    Vydané v Expert systems with applications (15.05.2023)
    “… A self-adaptive genetic algorithm is an evolutionary algorithm in which some or all of the algorithm’s parameters are evolved over the course of its execution…”
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