TY - BOOK UR - http://lib.ugent.be/catalog/ebk01:3710000000873007 ID - ebk01:3710000000873007 ET - 2nd ed. 2016. LA - eng TI - Computational Intelligence A Methodological Introduction PY - 2016 SN - 9781447172963 AU - Kruse, Rudolf. author. AU - Borgelt, Christian. author. AU - Braune, Christian. author. AU - Mostaghim, Sanaz. author. AU - Steinbrecher, Matthias. author. AB - Introduction -- Part I: Neural Networks -- Introduction -- Threshold Logic Units -- General Neural Networks -- Multi-Layer Perceptrons -- Radial Basis Function Networks -- Self-Organizing Maps -- Hopfield Networks -- Recurrent Networks -- Mathematical Remarks for Neural Networks -- Part II: Evolutionary Algorithms -- Introduction to Evolutionary Algorithms -- Elements of Evolutionary Algorithms -- Fundamental Evolutionary Algorithms -- Computational Swarm Intelligence -- Part III: Fuzzy Systems -- Fuzzy Sets and Fuzzy Logic -- The Extension Principle -- Fuzzy Relations -- Similarity Relations -- Fuzzy Control -- Fuzzy Data Analysis -- Part IV: Bayes and Markov Networks -- Introduction to Bayes Networks -- Elements of Probability and Graph Theory -- Decompositions -- Evidence Propagation -- Learning Graphical Models -- Belief Revision -- Decision Graphs. AB - This authoritative textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition to the definitive textbook on Computational Intelligence has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. Topics and features: Provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools Contains numerous classroom-tested examples and definitions throughout the text Presents useful insights into all that is necessary for the successful application of computational intelligence methods Explains the theoretical background underpinning proposed solutions to common problems Discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms Reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models This accessible text is an essential reference for students of artificial intelligence and intelligent systems, and a valuable resource for all researchers and practitioners seeking a self-study primer on computational intelligence. Rudolf Kruse and Sanaz Mostaghim are professors at the Department of Computer Science of the Otto von Guericke University of Magdeburg, Germany. Christian Borgelt is a principal researcher, and Christian Braune is a research assistant at the same institution. Matthias Steinbrecher is with SAP SE, Potsdam, Germany. ER -Download RIS file
00000nam a22000005i 4500 | |||
001 | 978-1-4471-7296-3 | ||
003 | DE-He213 | ||
005 | 20160916101412.0 | ||
007 | cr nn 008mamaa | ||
008 | 160916s2016 xxk| s |||| 0|eng d | ||
020 | a 9781447172963 9 978-1-4471-7296-3 | ||
024 | 7 | a 10.1007/978-1-4471-7296-3 2 doi | |
050 | 4 | a Q334-342 | |
050 | 4 | a TJ210.2-211.495 | |
072 | 7 | a UYQ 2 bicssc | |
072 | 7 | a TJFM1 2 bicssc | |
072 | 7 | a COM004000 2 bisacsh | |
082 | 4 | a 006.3 2 23 | |
100 | 1 | a Kruse, Rudolf. e author. | |
245 | 1 | a Computational Intelligence h [electronic resource] : b A Methodological Introduction / c by Rudolf Kruse, Christian Borgelt, Christian Braune, Sanaz Mostaghim, Matthias Steinbrecher. | |
250 | a 2nd ed. 2016. | ||
264 | 1 | a London : b Springer London : b Imprint: Springer, c 2016. | |
300 | a XIII, 564 p. 255 illus. b online resource. | ||
336 | a text b txt 2 rdacontent | ||
337 | a computer b c 2 rdamedia | ||
338 | a online resource b cr 2 rdacarrier | ||
347 | a text file b PDF 2 rda | ||
490 | 1 | a Texts in Computer Science, x 1868-0941 | |
505 | a Introduction -- Part I: Neural Networks -- Introduction -- Threshold Logic Units -- General Neural Networks -- Multi-Layer Perceptrons -- Radial Basis Function Networks -- Self-Organizing Maps -- Hopfield Networks -- Recurrent Networks -- Mathematical Remarks for Neural Networks -- Part II: Evolutionary Algorithms -- Introduction to Evolutionary Algorithms -- Elements of Evolutionary Algorithms -- Fundamental Evolutionary Algorithms -- Computational Swarm Intelligence -- Part III: Fuzzy Systems -- Fuzzy Sets and Fuzzy Logic -- The Extension Principle -- Fuzzy Relations -- Similarity Relations -- Fuzzy Control -- Fuzzy Data Analysis -- Part IV: Bayes and Markov Networks -- Introduction to Bayes Networks -- Elements of Probability and Graph Theory -- Decompositions -- Evidence Propagation -- Learning Graphical Models -- Belief Revision -- Decision Graphs. | ||
520 | a This authoritative textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition to the definitive textbook on Computational Intelligence has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. Topics and features: Provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools Contains numerous classroom-tested examples and definitions throughout the text Presents useful insights into all that is necessary for the successful application of computational intelligence methods Explains the theoretical background underpinning proposed solutions to common problems Discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms Reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models This accessible text is an essential reference for students of artificial intelligence and intelligent systems, and a valuable resource for all researchers and practitioners seeking a self-study primer on computational intelligence. Rudolf Kruse and Sanaz Mostaghim are professors at the Department of Computer Science of the Otto von Guericke University of Magdeburg, Germany. Christian Borgelt is a principal researcher, and Christian Braune is a research assistant at the same institution. Matthias Steinbrecher is with SAP SE, Potsdam, Germany. | ||
650 | a Computer science. | ||
650 | a Artificial intelligence. | ||
650 | a Applied mathematics. | ||
650 | a Engineering mathematics. | ||
650 | 1 | 4 | a Computer Science. |
650 | 2 | 4 | a Artificial Intelligence (incl. Robotics). |
650 | 2 | 4 | a Appl.Mathematics/Computational Methods of Engineering. |
700 | 1 | a Borgelt, Christian. e author. | |
700 | 1 | a Braune, Christian. e author. | |
700 | 1 | a Mostaghim, Sanaz. e author. | |
700 | 1 | a Steinbrecher, Matthias. e author. | |
710 | 2 | a SpringerLink (Online service) | |
773 | t Springer eBooks | ||
776 | 8 | i Printed edition: z 9781447172949 | |
830 | a Texts in Computer Science, x 1868-0941 | ||
856 | 4 | u http://dx.doi.org/10.1007/978-1-4471-7296-3 | |
912 | a ZDB-2-SCS | ||
950 | a Computer Science (Springer-11645) |
All data below are available with an Open Data Commons Open Database License. You are free to copy, distribute and use the database; to produce works from the database; to modify, transform and build upon the database. As long as you attribute the data sets to the source, publish your adapted database with ODbL license, and keep the dataset open (don't use technical measures such as DRM to restrict access to the database).
The datasets are also available as weekly exports.