000			03854nam a22004815i 4500
001			u373183
003			SIRSI
005			20160812084134.0
007			cr nn 008mamaa
008			100301s2010 gw | s |||| 0|eng d
020			_a9783540699132 _9978-3-540-69913-2
040			_cMX-MeUAM
050		4	_aQ342
082	0	4	_a006.3 _223
100	1		_aKordon, Arthur. _eauthor.
245	1	0	_aApplying Computational Intelligence _h[recurso electrónico] : _bHow to Create Value / _cby Arthur Kordon.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXXII, 459p. 20 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aComputational Intelligence in a Nutshell -- Artificial vs. Computational Intelligence -- A Roadmap Through the Computational Intelligence Maze -- Let's Get Fuzzy -- Machine Learning: The Ghost in the Learning Machine -- Evolutionary Computation: The Profitable Gene -- Swarm Intelligence: The Benefits of Swarms -- Intelligent Agents: The Computer Intelligence Agency (CIA) -- Computational Intelligence Creates Value -- Why We Need Intelligent Solutions -- Competitive Advantages of Computational Intelligence -- Issues in Applying Computational Intelligence -- Computational Intelligence Application Strategy -- Integrate and Conquer -- How to Apply Computational Intelligence -- Computational Intelligence Marketing -- Industrial Applications of Computational Intelligence -- The Future of Computational Intelligence -- Future Directions of Applied Computational Intelligence.
520			_aIn theory, there is no difference between theory and practice. But, in practice, there is. Jan L. A. van de Snepscheut The ?ow of academic ideas in the area of computational intelligence has penetrated industry with tremendous speed and persistence. Thousands of applications have proved the practical potential of fuzzy logic, neural networks, evolutionary com- tation, swarm intelligence, and intelligent agents even before their theoretical foundation is completely understood. And the popularity is rising. Some software vendors have pronounced the new machine learning gold rush to “Transfer Data into Gold”. New buzzwords like “data mining”, “genetic algorithms”, and “swarm optimization” have enriched the top executives’ vocabulary to make them look more “visionary” for the 21st century. The phrase “fuzzy math” became political jargon after being used by US President George W. Bush in one of the election debates in the campaign in 2000. Even process operators are discussing the perf- mance of neural networks with the same passion as the performance of the Dallas Cowboys. However, for most of the engineers and scientists introducing computational intelligence technologies into practice, looking at the growing number of new approaches, and understanding their theoretical principles and potential for value creation becomes a more and more dif?cult task.
650		0	_aEngineering.
650		0	_aData mining.
650		0	_aArtificial intelligence.
650		0	_aEngineering design.
650		0	_aTechnology.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aTechnology Management.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aEngineering Design.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540699101
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-540-69913-2
596			_a19
942			_cLIBRO_ELEC
999			_c201063 _d201063