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Computational Intelligence in Intelligent Data Analysis [electronic resource] / edited by Christian Moewes, Andreas N�urnberger.

Contributor(s): Moewes, Christian [editor.] | N�urnberger, Andreas [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 445Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: X, 306 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642323782.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Information Systems Applications (incl. Internet)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Part I Fuzzy Data Analysis -- Part II Hybrid Intelligent Systems -- Part III Uncertainty in Knowledge-based Systems -- Part IV Intelligent Data Analysis -- Part V Applications -- Part VI Closing Remarks.
In: Springer eBooksSummary: Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.
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Part I Fuzzy Data Analysis -- Part II Hybrid Intelligent Systems -- Part III Uncertainty in Knowledge-based Systems -- Part IV Intelligent Data Analysis -- Part V Applications -- Part VI Closing Remarks.

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.

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