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008 140320s2014 gw | s |||| 0|eng d
020 _a9783319059457
024 7 _a10.1007/978-3-319-05945-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
245 1 0 _aAdvances in Soft Computing, Intelligent Robotics and Control
_h[libro electrónico] /
_cedited by Janos Fodor, Robert Fuller.
260 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _axviii, 321 p. :
_bil.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTopics in Intelligent Engineering and Informatics,
_x2193-9411 ;
_v8
505 0 _aIntelligent Robotics and Control -- Soft Computing -- Applied Mathematics.
520 _aSoft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability, and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule interpolation, subjective weights based meta learning in multi criteria decision making, swarm-based heuristics for an area exploration and knowledge driven adaptive product representations. The last part addresses different problems, issues and methods of applied mathematics. This includes perturbation estimates for invariant subspaces of Hessenberg matrices, uncertainty and nonlinearity modelling by probabilistic metric spaces and comparison and visualization of the DNA of six primates.
650 0 _aEngineering.
_9259622
650 0 _aComputational intelligence.
_9259845
650 0 _aControl engineering.
_9259595
650 0 _aRobotics.
_9259596
650 0 _aAutomation.
_9259787
650 2 4 _aControl.
_9263886
700 1 _aFodor, Janos,
_eed.
_9261249
700 1 _aFuller, Robert,
_eed.
_9261250
776 0 8 _iPrinted edition:
_z9783319059440
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-05945-7
912 _aZDB-2-ENG
929 _aCOM
942 _cEBK
999 _aSKV
_c27928
_d27928