000 03831nam a22004935i 4500
001 978-3-642-33021-6
003 DE-He213
005 20200421112231.0
007 cr nn 008mamaa
008 120914s2013 gw | s |||| 0|eng d
020 _a9783642330216
_9978-3-642-33021-6
024 7 _a10.1007/978-3-642-33021-6
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aRecent Advances on Hybrid Intelligent Systems
_h[electronic resource] /
_cedited by Oscar Castillo, Patricia Melin, Janusz Kacprzyk.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXII, 572 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v451
505 0 _aPart I Hybrid Intelligent Systems for Control and Robotics -- Part II Hybrid Intelligent Systems for Pattern Recognition and Time Series Prediction -- Part III Bio-Inspired and Genetic Optimization Methods .-Part IV Intelligent Optimization and Applications -- Part V Evolutionary Methods and Intelligent Computing .
520 _aThis book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.  .
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aCastillo, Oscar.
_eeditor.
700 1 _aMelin, Patricia.
_eeditor.
700 1 _aKacprzyk, Janusz.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642330209
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v451
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-33021-6
912 _aZDB-2-ENG
942 _cEBK
999 _c58018
_d58018