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Metaheuristics in water, geotechnical and transport engineering

  1. Title statementMetaheuristics in water, geotechnical and transport engineering / edited by Xin-She Yang and others
    Edition statementFirst edition
    PublicationAmsterdam ; Boston : Elsevier, 2012
    Phys.des.1 online zdroj (xvii, 484 stran) : ilustrace
    ISBN9780123983176 (online ; pdf)
    0123983177
    9781283619912
    1283619911
    EditionElsevier insights
    Internal Bibliographies/Indexes NoteObsahuje bibliografické odkazy
    Contentspt. 1. Water resources -- pt. 2. Geotechnical engineering -- pt. 3. Transport engineering.
    Notes to AvailabilityPřístup pouze pro oprávněné uživatele
    NoteZpůsob přístupu: World Wide Web
    DefektyeBooks on EBSCOhost
    Another responsib. Yang, Xin-She (editor)
    Subj. Headings matematická optimalizace mathematical optimization
    Form, Genre elektronické knihy electronic books
    Conspect519.1/.8 - Kombinatorika. Teorie grafů. Matematická statistika. Operační výzkum. Matematické modelování
    UDC 519.85 , (0.034.2:08)
    CountryNizozemsko ; Spojené státy americké
    Languageangličtina
    Document kindElectronic sources
    URLhttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=484589
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    "Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are often large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems. This book examines the latest developments of metaheuristics and their applications in water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks."--Publisher's website.

    pt. 1. Water resources -- pt. 2. Geotechnical engineering -- pt. 3. Transport engineering.

Number of the records: 1  

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