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S4: Intelligent Environmental Decision Support Systems

Page: Main.S4 - Last Modified : Mon, 04 Aug 08

Main.S4 History

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Rick Sojda, Northern Rocky Mountain Science Center, US Dept. of the Interior - Geological Survey/Ecology Dept., Montana State University, USA
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Rick Sojda, NRMSC, US Dept. of the Interior - Geological Survey/Ecology Dept., Montana State University, USA
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- Jean Philippe Steyer, Process Engineering And Control Engineering (PEACE) group, Environmental Biotechnology Laboratory - INRA, France
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- Jean Philippe Steyer, PEACE group, Environmental Biotechnology Laboratory - INRA, France
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Description

The session will focus a discussion platform for Artificial Intelligence (AI) and Environmental researchers involved in the development of applications in the Intelligent Environmental Decision Support Systems (IEDSS) area. Nowadays, AI techniques such as rule-based reasoning, fuzzy models, case-based reasoning, qualitative reasoning, artificial neural networks, genetic algorithms and programming, model-based reasoning, bayesian networks, multiagent systems, etc., enable the construction of reliable and real applications. IEDSS are present in the environmental management process at different levels such as hazard identification, risk assessment, risk evaluation and intervention decision-making.

Session participants may come from all environmental science and AI fields.

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Methodologies and frameworks for the development of IEDSSs. Integration of AI and Statistical/Mathematical models in IEDSSs. Model recomendation in IEDSSs. Benchmarking and validation of IEDSSs.

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  • Methodologies and frameworks for the development of IEDSSs
  • Integration of AI and Statistical/Mathematical models in IEDSSs
  • Model recomendation in IEDSSs
  • Benchmarking and validation of IEDSSs.

Description

The session will focus a discussion platform for Artificial Intelligence (AI) and Environmental researchers involved in the development of applications in the Intelligent Environmental Decision Support Systems (IEDSS) area. Nowadays, AI techniques such as rule-based reasoning, fuzzy models, case-based reasoning, qualitative reasoning, artificial neural networks, genetic algorithms and programming, model-based reasoning, bayesian networks, multiagent systems, etc., enable the construction of reliable and real applications. IEDSS are present in the environmental management process at different levels such as hazard identification, risk assessment, risk evaluation and intervention decision-making, but there is neither well defined methodology or framework for the development of IEDSSs nor for Model integration nor for Model recomendatiom techniques nor for Benchmarking and validation of IEDSSs. These are the open challenges to be addressed by the session papers.

Session participants may come from all environmental science and AI fields.

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October 12, 2007, at 01:10 AM by 89.131.108.230 -
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"The session will focus a discussion platform for Artificial Intelligence (AI) and Environmental researchers involved in the development of applications in the Intelligent Environmental Decision Support Systems (IEDSS) area. Nowadays, AI techniques such as rule-based reasoning, fuzzy models, case-based reasoning, qualitative reasoning, artificial neural networks, genetic algorithms and programming, model-based reasoning, bayesian networks, multiagent systems, etc., enable the construction of reliable and real applications. IEDSS are present in the environmental management process at different levels such as hazard identification, risk assessment, risk evaluation and intervention decision-making.

Session participants may come from all environmental science and AI fields."

to:

The session will focus a discussion platform for Artificial Intelligence (AI) and Environmental researchers involved in the development of applications in the Intelligent Environmental Decision Support Systems (IEDSS) area. Nowadays, AI techniques such as rule-based reasoning, fuzzy models, case-based reasoning, qualitative reasoning, artificial neural networks, genetic algorithms and programming, model-based reasoning, bayesian networks, multiagent systems, etc., enable the construction of reliable and real applications. IEDSS are present in the environmental management process at different levels such as hazard identification, risk assessment, risk evaluation and intervention decision-making.

Session participants may come from all environmental science and AI fields.

October 12, 2007, at 01:10 AM by 89.131.108.230 -
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