A Linear Genetic Programming Approach for Modelling Electricity Demand Prediction in Victoria-Reference-Cited by-同舟云学术

A Linear Genetic Programming Approach for Modelling Electricity Demand Prediction in Victoria

Published:2002 Issue: Volume: Page:379-393
ISSN:
Container-title:Hybrid Information Systems
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Author:

Bhattacharya Maumita,Abraham Ajith,Nath Baikunth

Publisher

Physica-Verlag HD

Link

http://link.springer.com/content/pdf/10.1007/978-3-7908-1782-9_28

Reference20 articles.

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2. A. Abraham, B. Nath, A Neuro-Fuzzy Approach for Forecasting Electricity Demand in Victoria, Applied Soft Computing Journal, Elsevier Science, Volume 1 /2, 2001, pp. 127–138.

3. L.M. Deschaine, F.A. Zafran, J.J. Patel, D. Amick, R. Pettit, SAIC, F.D. Francone, P. Nordin, E. Dukes, L.V. Fausett, Solving the Unsolved-Using Machine Learningto Model a Complex Production Process-Case Example Applying Three Machine Learning Techniques, Society for Computer Simulation’s Advanced Simulation Technology Conference, Washington, DC, USA, April 2000.

4. J.R. Koza, F.H. Bennett, D. Andre, M.A. Keane, GENETIC PROGRAMMING-III — Darwinian Invention and Problem Solving, Morgan Kaufmann Publishers, Inc., 1999

5. F.D. Francone, P. Nordin, W. Banzhaf, E. DILKES, L.M. Deschaine, AIM LearningTM Adaptive, Real-Time, Control Technologies. Society for Computer Simulation’s Advanced Simulation Technology Conference, Washington, DC, USA, April 2000.

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