applying computational intelligence (8 Ergebnisse)

Taschenbuch. Zustand: Neu. Hybrid Strategies for Improving Bayesian Networks | Applying Mathematical and Computational Intelligence Models to Optimize and Extend the Modelling and Applicability | Ádamo Lima Santana (u. a.) | Taschenbuch | 80 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844323146 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

hardcover. Zustand: Very Good.

Taschenbuch. Zustand: Neu. Applying Computational Intelligence | How to Create Value | Arthur Kordon | Taschenbuch | xxii | Englisch | 2014 | Springer Berlin | EAN 9783642424267 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Buch. Zustand: Neu. Neuware -In 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 484 pp. Englisch.

Hardcover. Zustand: Brand New. 1st edition. 459 pages. 9.25x6.50x1.25 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In 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.

Hardcover. Zustand: Brand New. 310 pages. 9.00x6.00x1.00 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In 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.