A self-organizing maps multivariate spatio-temporal approach for the classification of atmospheric conditions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7666 LNCS, Issue PART 4, 2012, Pages 544-551

  Philippopoulos, Kostas ^a   Deligiorgi, Despina ^a  

^a UNIVERSITY OF ATHENS   (Greece)

Author keywords

atmospheric circulation; pattern recognition; self organizing maps; synoptic climatology

Indexed keywords

ANALYTICAL DESCRIPTION; ATMOSPHERIC CIRCULATION; ATMOSPHERIC CIRCULATION PATTERNS; ATMOSPHERIC CONDITIONS; ATMOSPHERIC PHYSICS; CLUSTERING APPROACH; DATA SETS; DEWPOINT TEMPERATURE; GEOPOTENTIALS; MESOSCALE; SEA LEVEL PRESSURE; SEASONALITY; SIMILAR PATTERN; SOM ALGORITHMS; SPATIO-TEMPORAL; SPATIO-TEMPORAL APPROACH; SPECIFIC HUMIDITY; SUBDOMAIN; SYNOPTIC CLIMATOLOGY; TWO-DIMENSIONAL LATTICES;

CLIMATOLOGY; CONFORMAL MAPPING; DATA PROCESSING; GEOPHYSICS; PATTERN RECOGNITION; SEA LEVEL;

ATMOSPHERIC HUMIDITY;

EID: 84869021994     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-34478-7_66     Document Type: Conference Paper

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