Staffordshire University logo
STORE - Staffordshire Online Repository

Refinement of artificial intelligence-based systems for diagnosing and predicting river health

PAISLEY, Martin and TRIGG, David and MARTIN, Ray and WALLEY, William and ANDRIAENSSENS, Veronique and BUXTON, Robert and O'CONNOR, Mark (2011) Refinement of artificial intelligence-based systems for diagnosing and predicting river health. Environment Agency, Bristol. ISBN 9781849112437

[img]
Preview
Text
scho0911bubl-e-e.pdf

Download (6MB) | Preview

Abstract or description

Environment Agency Technical Report EMC/WP06 077.

This report presents the results of a project funded by the Environment Agency which builds on the previous creation of two software systems to diagnose and predict river health from biological and environmental data, namely the River Pressure Diagnostic System (RPDS) and the River Pressure Bayesian Belief Network (RPBBN). RPDS is a pattern recognition system to diagnose likely pressures at a river site. RPBBN is a reasoning system that can diagnose chemical concentrations from a biological community, or predict likely changes in a biological community from changes in chemical concentrations.
An early aim of our project was to use the RPDS database to define chemical standards needed to protect ecological quality. This was achieved by developing Thresholder, a software application which searches the 1995 river survey database to determine the chemical concentrations needed to support the invertebrate fauna predicted by RIVAPCS (River Invertebrate Prediction and Classification System) at all general quality assessment sites.
A second early objective was to use the same database to help determine potential reference sites to act as targets for temporal trajectories in RPDS.

The main aims of the project were to enhance the software systems RPDS and RPBBN. The specific objectives were as follows:
• Substantially extend the dataset on which the data models are based.
• Revise and test the data models on which the systems are based.
• Extend the functionality of the two systems and combine into one ‘integrated system’.

Environmental Health Report: SC030189

Item Type: Book / Proceeding
Subjects: G400 Computer Science
G500 Information Systems
G700 Artificial Intelligence
Faculty: Previous Faculty of Computing, Engineering and Sciences > Computing
Related URLs:
Depositing User: David TRIGG
Date Deposited: 05 Nov 2013 08:06
Last Modified: 18 Nov 2013 15:09
URI: http://eprints.staffs.ac.uk/id/eprint/1769

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000