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03804nam a22005655i 4500 |
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978-3-642-00185-7 |
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DE-He213 |
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20151204173947.0 |
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cr nn 008mamaa |
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100301s2009 gw | s |||| 0|eng d |
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|a 9783642001857
|9 978-3-642-00185-7
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|a 10.1007/978-3-642-00185-7
|2 doi
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|d GrThAP
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|a QA71-90
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|a PBKS
|2 bicssc
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|a MAT006000
|2 bisacsh
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|a 518
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|a Music-Inspired Harmony Search Algorithm
|h [electronic resource] :
|b Theory and Applications /
|c edited by Zong Woo Geem.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2009.
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|a X, 206 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 191
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|a Harmony Search as a Metaheuristic Algorithm -- Overview of Applications and Developments in the Harmony Search Algorithm -- Harmony Search Methods for Multi-modal and Constrained Optimization -- Solving NP-Complete Problems by Harmony Search -- Harmony Search Applications in Mechanical, Chemical and Electrical Engineering -- Optimum Design of Steel Skeleton Structures -- Harmony Search Algorithms for Water and Environmental Systems -- Identification of Groundwater Parameter Structure Using Harmony Search Algorithm -- Modified Harmony Methods for Slope Stability Problems -- Harmony Search Algorithm for Transport Energy Demand Modeling -- Sound Classification in Hearing Aids by the Harmony Search Algorithm -- Harmony Search in Therapeutic Medical Physics.
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|a Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have recently turned their interests into metaheuristic algorithms that have been inspired by natural phenomena such as evolution, animal behavior, or metallic annealing. This book especially focuses on a music-inspired metaheuristic algorithm, harmony search. Interestingly, there exists an analogy between music and optimization: each musical instrument corresponds to each decision variable; musical note corresponds to variable value; and harmony corresponds to solution vector. Just like musicians in Jazz improvisation play notes randomly or based on experiences in order to find fantastic harmony, variables in the harmony search algorithm have random values or previously-memorized good values in order to find optimal solution.
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| 650 |
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|a Mathematics.
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| 650 |
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|a Music.
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| 650 |
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|a Algorithms.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Computer mathematics.
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| 650 |
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|a Mathematical models.
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|a Applied mathematics.
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|a Engineering mathematics.
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4 |
|a Mathematics.
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| 650 |
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|a Computational Mathematics and Numerical Analysis.
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| 650 |
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|a Mathematical Modeling and Industrial Mathematics.
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| 650 |
2 |
4 |
|a Algorithm Analysis and Problem Complexity.
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| 650 |
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|a Appl.Mathematics/Computational Methods of Engineering.
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| 650 |
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|a Artificial Intelligence (incl. Robotics).
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| 650 |
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|a Music.
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| 700 |
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|a Geem, Zong Woo.
|e editor.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9783642001840
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| 830 |
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 191
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-642-00185-7
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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