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  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    UID:
    b3kat_BV046062589
    Format: 1 Online-Ressource (XV, 299 p. 108 illus., 58 illus. in color)
    ISBN: 9783030150709
    Series Statement: Adaptation, Learning, and Optimization 23
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-15069-3
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-15071-6
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-15072-3
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cham :Springer International Publishing :
    UID:
    almafu_9959767540102883
    Format: 1 online resource (305 pages)
    Edition: 1st ed. 2019.
    ISBN: 3-030-15070-4
    Series Statement: Adaptation, Learning, and Optimization, 23
    Content: Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence. This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems. .
    Note: Brain Storm Optimization Algorithms: More Questions than Answers -- Brain Storm Optimization for Test Task Scheduling Problem -- Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networks -- Multi-objective Brain Storm Optimization Based on Differential Evolution for Environmental/Economic Dispatch Problem -- Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation -- Brain Storm Algorithm Combined with Covariance Matrix Adaptation Evolution Strategy for Optimization -- A Feature Extraction Method Based on BSO Algorithm for Flight Data -- Brain Storm Optimization Algorithms for Solving Equations Systems -- StormOptimus: A Single Objective Constrained Optimizer Based on Brainstorming Process for VLSI Circuits -- Brain Storm Optimization Algorithms for Flexible Job Shop Scheduling Problem -- Enhancement of Voltage Stability using FACTS Devices in Electrical Transmission System with Optimal Rescheduling of Generators by Brain Storm Optimization Algorithm.
    Additional Edition: ISBN 3-030-15069-0
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    almahu_9948105336902882
    Format: XV, 299 p. 108 illus., 58 illus. in color. , online resource.
    ISBN: 9783030150709
    Series Statement: Adaptation, Learning, and Optimization, 23
    Content: Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence. This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems. .
    Note: Brain Storm Optimization Algorithms: More Questions than Answers -- Brain Storm Optimization for Test Task Scheduling Problem -- Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networks -- Multi-objective Brain Storm Optimization Based on Differential Evolution for Environmental/Economic Dispatch Problem -- Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation -- Brain Storm Algorithm Combined with Covariance Matrix Adaptation Evolution Strategy for Optimization -- A Feature Extraction Method Based on BSO Algorithm for Flight Data -- Brain Storm Optimization Algorithms for Solving Equations Systems -- StormOptimus: A Single Objective Constrained Optimizer Based on Brainstorming Process for VLSI Circuits -- Brain Storm Optimization Algorithms for Flexible Job Shop Scheduling Problem -- Enhancement of Voltage Stability using FACTS Devices in Electrical Transmission System with Optimal Rescheduling of Generators by Brain Storm Optimization Algorithm.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783030150693
    Additional Edition: Printed edition: ISBN 9783030150716
    Additional Edition: Printed edition: ISBN 9783030150723
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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