Artificial Intelligence techniques: An introduction to their use for modelling environmental systems

Serena H. Chen; Anthony J. Jakeman; John P. Norton

doi:10.1016/j.matcom.2008.01.028

Artificial Intelligence techniques: An introduction to their use for modelling environmental systems

Serena H. Chen
, Anthony J. Jakeman^*
, John P. Norton

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

282 Citations (Scopus)

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.

Original language	English
Pages (from-to)	379-400
Number of pages	22
Journal	Mathematics and Computers in Simulation
Volume	78
Issue number	2-3
DOIs	https://doi.org/10.1016/j.matcom.2008.01.028
Publication status	Published - Jul 2008

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10.1016/j.matcom.2008.01.028

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title = "Artificial Intelligence techniques: An introduction to their use for modelling environmental systems",

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, Environmental modelling, Multi-agent",

author = "Chen, \{Serena H.\} and Jakeman, \{Anthony J.\} and Norton, \{John P.\}",

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AU - Jakeman, Anthony J.

AU - Norton, John P.

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N2 - 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.

AB - 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.

KW - Case-based reasoning

KW - Cellular automata

KW - Environmental modelling

KW - Multi-agent

UR - https://www.scopus.com/pages/publications/43449100655

U2 - 10.1016/j.matcom.2008.01.028

DO - 10.1016/j.matcom.2008.01.028

M3 - Article

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SP - 379

EP - 400

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

IS - 2-3

ER -

Artificial Intelligence techniques: An introduction to their use for modelling environmental systems

Abstract

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