EEIE: an expert system for environmental impact evaluation

Pazos Sierra, Alejandro, Santos del Riego, Antonino, Rivas-Feal, Antonio, Maojo Garcia, Victor Manuel ORCID: https://orcid.org/0000-0001-5103-4292 and Segovia, Javier (1993). EEIE: an expert system for environmental impact evaluation. In: "Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology", Oct 28-31 1993, San Diego, California, USA. ISBN 0-7803-1377-1. pp. 1453-1454. https://doi.org/10.1109/IEMBS.1993.978725.

Description

Title: EEIE: an expert system for environmental impact evaluation
Author/s:
  • Pazos Sierra, Alejandro
  • Santos del Riego, Antonino
  • Rivas-Feal, Antonio
  • Maojo Garcia, Victor Manuel https://orcid.org/0000-0001-5103-4292
  • Segovia, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology
Event Dates: Oct 28-31 1993
Event Location: San Diego, California, USA
Title of Book: Proceedings of the 15th International Conference on IEEE Engineering in Medicine and Biology Society
Date: 1993
ISBN: 0-7803-1377-1
Volume: 15
Subjects:
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The environment has a very important role in public health (i.e: cardiovascular pathology, discomfort, ...). Doing and appropiate Environmental Impact Evaluation of man actions will help to preserve public health of possible harmfull effects of these actions. Environmental Impact Evaluation using Leopold and Battelle methods. has been implemented in the EEIE expert system. It's an efficient system to suggest, characterize and evaluate hypothesis associated with environmental impact. These hypothesis are stablished in order to link project actions with environmental factors, as well as to determine the involucrate corrective actions. The set of hypothesis obtained is grouped together one obtained by a back propagation artificial neural network (ANN) and then EEIE evaluate every hypothesis. Therefore, EEIE presented here generalize expert knowledge of the environmental impact domain.

More information

Item ID: 75924
DC Identifier: https://oa.upm.es/75924/
OAI Identifier: oai:oa.upm.es:75924
DOI: 10.1109/IEMBS.1993.978725
Official URL: https://ieeexplore.ieee.org/document/978725
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 18 Sep 2023 12:21
Last Modified: 18 Sep 2023 12:21
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