000 03778nam a22004935i 4500
001 978-3-642-27467-1
003 DE-He213
005 20140220083308.0
007 cr nn 008mamaa
008 120127s2012 gw | s |||| 0|eng d
020 _a9783642274671
_9978-3-642-27467-1
024 7 _a10.1007/978-3-642-27467-1
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aSanchez, Ernesto.
_eauthor.
245 1 0 _aIndustrial Applications of Evolutionary Algorithms
_h[electronic resource] /
_cby Ernesto Sanchez, Giovanni Squillero, Alberto Tonda.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aXII, 114p. 21 illus., 12 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v34
505 0 _aIntroduction -- Resources -- Automatic software verification -- Post-silicon speed-path analysis in modern microprocessors through genetic programming -- Antenna array synthesis with Evolutionary Algorithms -- Drift correction of chemical sensors -- Development of on-line test sets for microprocessors -- Uncovering path delay faults with Multi-Objective EAs -- Software-Based Self Testing of system peripherals -- Software-based self-testing on microprocessors.
520 _a"Industrial applications of evolutionary algorithms" is intended as a resource for both experienced users of evolutionary algorithms and researchers that are beginning to approach these fascinating optimization techniques. Experienced users will find interesting details of real-world problems, advice on solving issues related to fitness computation or modeling, and suggestions on how to set the appropriate parameters to reach optimal solutions. Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of several classes of evolutionary algorithms exploited to solve different problems. Inside, scholars will find useful examples on how to fill the gap between purely theoretical examples and industrial problems. The collection of case studies presented is also extremely appealing for anyone interested in Evolutionary Computation, but without direct access to extensive technical literature on the subject. After the introduction, each chapter in the book presents a test case, and is organized so that it can be read independently from the rest: all the information needed to understand the problem and the approach is reported in each part. Chapters are grouped by three themes of particular interest for real-world applications, namely prototype-based validation, reliability and test generation. The authors hope that this volume will help to expose the flexibility and efficiency of evolutionary techniques, encouraging more companies to adopt them; and that, most of all, you will enjoy your reading.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
700 1 _aSquillero, Giovanni.
_eauthor.
700 1 _aTonda, Alberto.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642274664
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v34
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-27467-1
912 _aZDB-2-ENG
999 _c102596
_d102596