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Verlag: LAP Lambert Academic Publishing, 2010
ISBN 10: 384337144X ISBN 13: 9783843371445
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Computational Intelligence in Computer Aided Medical Diagnosis | Cognitive clinical decision-making with Neuro-Fuzzy-Genetic systems, Weight initialization and Advanced image processing techniques | Latha Parthiban | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783843371445 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Verlag: Sankt Augustin, infix, 1998
Sprache: Englisch
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In den WarenkorbSoftcover/Paperback. Zustand: Gut. 384 S. Good condition. Sprache: Englisch Gewicht in Gramm: 825.
Verlag: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 384337144X ISBN 13: 9783843371445
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Computational Intelligence Systems and Applications | Neuro-Fuzzy and Fuzzy Neural Synergisms | Marian B. Gorzalczany | Taschenbuch | x | Englisch | 2012 | Physica | EAN 9783662003343 | Verantwortliche Person für die EU: Physica Verlag in Springer Science + Business Media, Tiergartenstr. 15-17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Zustand: Gut. 384 S., graph. Darst. Handschriftlicher Besitzvermerk auf der Vorsatzseite. Innen neuwertig. Proceedings in artificial intelligence ; 7. Aus dem Inhalt: Invited Lectures, Sets, Fuzzy Sets and Rough Sets, Session 1: Fuzzy Control, Session 2: Neutral Networks for Classification, Session 3: Fuzzy Logic in Data Analysis, Session 4: Fuzzy-Neuro Systems, Session 5: Applications, Session6: Theory and Foundations of Fuzzy-Logic, Session 7: Theory and Foundations of Neural Networks, Poster Presentations. Innen tadellos erhalten. deu B12-01-05B|GH52|8477DB Sprache: Deutsch Gewicht in Gramm: 444 24 cm. Original Broschur. Sehr gut erhalten.
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Buch. Zustand: Neu. Computational Intelligence Systems and Applications | Neuro-Fuzzy and Fuzzy Neural Synergisms | Marian B. Gorzalczany | Buch | x | Englisch | 2001 | Physica | EAN 9783790814392 | Verantwortliche Person für die EU: Physica Verlag in Springer Science + Business Media, Tiergartenstr. 15-17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.