KNOWLEDGE-BASED VALIDATION FOR HYDROLOGICAL INFORMATION SYSTEMS

Authors: Conejo, Ricardo; Guzmán, Eduardo; Pérez-de-la-Cruz, José-Luis

Source: Applied Artificial Intelligence, Volume 21, Number 8, September 2007 , pp. 803-830(28)

Publisher: Taylor and Francis Ltd

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Abstract:

The introduction of systems for automatic data acquisition to monitor and control hydrological basins is a qualitative change in the field of hydrology. The large amount of information available increases the number of processes that can be analyzed with a quantitative approach. In the past, hydrological data validation was done manually by applying the knowledge of experts in the field. This article proposes to solve this problem using AI techniques. As a result, a generic model is defined for the cognitive task of data validation. The model is then applied to a real case.

Document Type: Research article

DOI: http://dx.doi.org/10.1080/08839510701526582

Affiliations: 1: Departamento de Lenguajes y Ciencias de la Computación, E.T.S.I. Informática, Málaga, Spain

Publication date: 2007-09-01

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