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03423nam a2200505 4500 |
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978-3-7908-1868-0 |
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DE-He213 |
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20191025091823.0 |
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cr nn 008mamaa |
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131024s2000 gw | s |||| 0|eng d |
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|a 9783790818680
|9 978-3-7908-1868-0
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|a 10.1007/978-3-7908-1868-0
|2 doi
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|a Q334-342
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|a 006.3
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|a Jain, Professor Lakhmi C.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Innovative Teaching and Learning
|h [electronic resource] :
|b Knowledge-Based Paradigms /
|c by Professor Lakhmi C. Jain.
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| 250 |
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|a 1st ed. 2000.
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| 264 |
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|a Heidelberg :
|b Physica-Verlag HD :
|b Imprint: Physica,
|c 2000.
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| 300 |
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|a XII, 334 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 36
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| 505 |
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|a D. Tedman, L.C. Jain: An Introduction to Innovative Teaching and Learning -- R.S.T. Lee, J.N.K. Liu: Teaching and Learning the AI Modeling -- C.L. Karr, C. Sunal, C. Smith: Artificial Intelligence Techniques for an Interdisciplinary Science Course -- J.F. Vega-Riveros: On the Architecture of Intelligent Tutoring Systems and its Application to a Neural Networks Course -- V. Devedzic: Teaching Knowledge Modeling at the Graduate Level - a Case Study -- V. Devedzic, D. Radovic, L. Jerinic: Innovative Modeling Techniques for Intelligent Tutoring Systems -- J. Fulcher: Teaching Course on Artificial Neural Networks -- T. Hiyama: Innovative Education for Fuzzy Logic Stabilization of Electric Power Systems in a Matlab/Simulink Environment -- W.L. Goh, S.K. Amarasinghe: A Neural Network Wokbench for Teaching and Learning -- C.A. Higgins, F.Z. Mansouri: PRAM: A Courseware System for the Automatic Assessment of AI Programs.
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|a Presented are innovative teaching and learning techniques for the teaching of knowledge-based paradigms. The main knowledge-based intelligent paradigms are expert systems, artificial neural networks, fuzzy systems and evolutionary computing. Expert systems are designed to mimic the performance of biological systems. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimization applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge.
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|a Artificial intelligence.
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|a Information technology.
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|a Business-Data processing.
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a IT in Business.
|0 http://scigraph.springernature.com/things/product-market-codes/522000
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9783790824650
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| 776 |
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|i Printed edition:
|z 9783790812466
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| 776 |
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|i Printed edition:
|z 9783662003985
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| 830 |
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 36
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-7908-1868-0
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 912 |
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|a ZDB-2-BAE
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| 950 |
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|a Engineering (Springer-11647)
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