Knowledge-based validation for hydrological information systems

被引：1

作者：

Conejo, Ricardo ^{[1
]}

Guzman, Eduardo ^{[1
]}

Perez-de-la-Cruz, Jose-Luis ^{[1
]}

机构：

[1] ETSI Informat, Dept Lenguajes & Ciencias Comp, E-29071 Malaga, Spain

来源：

APPLIED ARTIFICIAL INTELLIGENCE | 2007年 / 21卷 / 08期

关键词：

FAILURE-DETECTION; FAULT-DETECTION; MANAGEMENT; REDUNDANCY; SENSORS; MODEL;

D O I：

10.1080/08839510701526582

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：803 / 830

页数：28

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