Artificial Intelligence techniques: An introduction to their use for modelling environmental systems
Serena H. Chen,
Anthony J. Jakeman and
John P. Norton
Mathematics and Computers in Simulation (MATCOM), 2008, vol. 78, issue 2, 379-400
Abstract:
Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model environmental systems. We review some of them and their environmental applicability, with examples and a reference list. The techniques covered are case-based reasoning, rule-based systems, artificial neural networks, fuzzy models, genetic algorithms, cellular automata, multi-agent systems, swarm intelligence, reinforcement learning and hybrid systems.
Keywords: Case-based reasoning; Cellular automata; Multi-agent; Environmental modelling (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (23)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475408000505
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:78:y:2008:i:2:p:379-400
DOI: 10.1016/j.matcom.2008.01.028
Access Statistics for this article
Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens
More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).