Soft computing models to identify typical meteorological days

Logic Journal of the IGPL

Volumn 19, Issue 2, 2011, Pages 373-383

  Corchado, Emilio ^a   Arroyo, Ángel ^b   Tricio, Verónica ^b  

^a UNIVERSITY OF SALAMANCA   (Spain)

^b UNIVERSITY OF BURGOS   (Spain)

Author keywords

Artificial neural networks; Atmospheric pollution; Meteorology; Soft computing; Statistical models

Indexed keywords

AIR POLLUTION; DATA HANDLING; METEOROLOGY; SOFT COMPUTING;

ATMOSPHERIC POLLUTION; METEOROLOGICAL CONDITION; METEOROLOGICAL DATA; METEOROLOGICAL PARAMETERS; METEOROLOGICAL VARIABLES; POLLUTION MEASUREMENT; SOFT COMPUTING MODELS; SOFT-COMPUTING; STATISTIC MODELING; TYPICAL DAY;

NEURAL NETWORKS;

EID: 79954556565     PISSN: 13670751     EISSN: 13689894     Source Type: Journal    
DOI: 10.1093/jigpal/jzq035     Document Type: Article

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