The synergy between classical and soft-computing techniques for time series prediction

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2972, Issue , 2004, Pages 30-39

  Rojas, I ^a   Rojas, F ^a   Pomares, H ^a   Herrera, L J ^a   Gonzalez J ^a   Valenzuela, O ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; ERROR ANALYSIS; FUZZY SETS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; TIME SERIES ANALYSIS; VECTORS; ARTIFICIAL INTELLIGENCE; FUNCTIONS; NEURAL NETWORKS; SOFT COMPUTING;

NEURAL SYSTEMS; REGRESSION WEIGHTS; SEQUENTIAL LEARNING ALGORITHMS; SOFT-COMPUTING TECHNIQUES; DYNAMICAL MODEL; INPUT-OUTPUT DATA; PROCESS INFORMATION; PSEUDO-GAUSSIAN; RADIAL BASIS FUNCTIONS; SOFTCOMPUTING TECHNIQUES; TIME SERIES PREDICTION;

COMPUTATIONAL METHODS; TIME SERIES;

EID: 9444239783     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24694-7_4     Document Type: Conference Paper

References (9)

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