Innovative Teaching and Learning Knowledge-Based Paradigms /
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 bi...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Heidelberg :
Physica-Verlag HD : Imprint: Physica,
2000.
|
Έκδοση: | 1st ed. 2000. |
Σειρά: | Studies in Fuzziness and Soft Computing,
36 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.