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100%: Marian B. Gorzalczany: Computational Intelligence Systems and Applications : Neuro-Fuzzy and Fuzzy Neural Synergisms (ISBN: 9783790818017) in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
69%: B. Gorzalczany, Marian and Gorzalczany, Marian B.: Computational Intelligence Systems Applications: Neuro-Fuzzy Fuzzy Neural Synergisms (Studies in Fuzziness Soft Computing) (ISBN: 9783662003343) Physica-Verlag, in Deutsch, Taschenbuch.Nur diese Ausgabe anzeigen…
69%: Gorzalczany, M. B.; Gorzaczany, Marian B. and Gorzalczany, Marian B.: Computational Intelligence Systems Applications: Neuro-Fuzzy Fuzzy Neural Synergisms (Studies in Fuzziness Soft Computing) (ISBN: 9783790814392) 2002, in Deutsch, Broschiert.Nur diese Ausgabe anzeigen…
Computational Intelligence Systems and Applications : Neuro-Fuzzy and Fuzzy Neural Synergisms
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Bester Preis: Fr. 5.89 (€ 6.03)¹ (vom 22.10.2019)1
Computational Intelligence Systems and Applications
~EN NW EB DLISBN: 9783790818017 bzw. 3790818011, vermutlich in Englisch, Springer Shop, neu, E-Book, elektronischer Download.
Lieferung aus: Italien, Lagernd, zzgl. Versandkosten.
Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "buried" in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "encoded" in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. eBook.
Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "buried" in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "encoded" in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. eBook.
2
Computational Intelligence Systems and Applications - Neuro-Fuzzy and Fuzzy Neural Synergisms
~EN NW EB DLISBN: 9783790818017 bzw. 3790818011, vermutlich in Englisch, Physica-Verlag HD, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Versandkostenfrei.
Computational Intelligence Systems and Applications: Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real- world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "e buried"e in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "e encoded"e in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. Englisch, Ebook.
Computational Intelligence Systems and Applications: Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real- world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "e buried"e in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "e encoded"e in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed. Englisch, Ebook.
3
Computational Intelligence Systems and Applications
DE PB NWISBN: 9783662003343 bzw. 3662003341, in Deutsch, Physica-Verlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
buecher.de GmbH & Co. KG, [1].
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Computational Intelligence Systems and Applications
DE PB NWISBN: 9783662003343 bzw. 3662003341, in Deutsch, Physica-Verlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
buecher.de GmbH & Co. KG, [1].
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
buecher.de GmbH & Co. KG, [1].
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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Computational Intelligence Systems and Applications. Neuro-Fuzzy and Fuzzy Neural Synergisms (2012)
DE PB USISBN: 9783662003343 bzw. 3662003341, in Deutsch, Taschenbuch, gebraucht.
Von Händler/Antiquariat, Herb Tandree Philosophy Books [17426], Stroud, UK, United Kingdom.
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Computational Intelligence Systems and Applications: Neuro-fuzzy and Fuzzy Neural Synergisms (Hardback) (2002)
DE HC NW RPISBN: 9783790814392 bzw. 3790814393, in Deutsch, Springer-Verlag Berlin and Heidelberg GmbH Co. KG, Germany, gebundenes Buch, neu, Nachdruck.
Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Versandkostenfrei.
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing)
DE HC NWISBN: 9783790814392 bzw. 3790814393, in Deutsch, gebundenes Buch, neu.
Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Hardcover)
DE HC NWISBN: 9783790814392 bzw. 3790814393, in Deutsch, gebundenes Buch, neu.
Von Händler/Antiquariat, ABC Books [9235530], Lowfield Heath, CRAWL, United Kingdom.
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Computational Intelligence Systems Applications: Neuro-Fuzzy Fuzzy Neural Synergisms (2014)
DE PB NWISBN: 9783662003343 bzw. 3662003341, in Deutsch, Taschenbuch, neu.
Von Händler/Antiquariat, Paperbackshop-US [8408184], Secaucus, NJ, U.S.A.
New Book. This item is printed on demand. Shipped from US This item is printed on demand.
New Book. This item is printed on demand. Shipped from US This item is printed on demand.
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Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms (Studies in Fuzziness and Soft Computing) (2012)
DE PB NWISBN: 9783662003343 bzw. 3662003341, in Deutsch, Taschenbuch, neu.
Von Händler/Antiquariat, Revaluation Books [2134736], Exeter, DEV, United Kingdom.
reprint edition. In Stock.
reprint edition. In Stock.
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