Using SOM and PCA for analysing and interpreting data from a P-removal SBR

Engineering Applications of Artificial Intelligence

Volumn 21, Issue 6, 2008, Pages 919-930

  Aguado, D ^a   Montoya, T ^a   Borras, L ^b   Seco, A ^b   Ferrer, J ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Diagnosis; PCA; Sequencing batch reactor; SOM; Wastewater

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; BIOLOGICAL WATER TREATMENT; CHEMICALS REMOVAL (WATER TREATMENT); CLUSTER ANALYSIS; CONFORMAL MAPPING; FINANCIAL DATA PROCESSING; MAPS; NONMETALS; PHOSPHORUS; RANDOM VARIABLES; SELF ORGANIZING MAPS; STRENGTH OF MATERIALS; WASTEWATER TREATMENT;

(E ,3E) PROCESS; (SPM) CLASSES; APPLIED (CO); BIOLOGICAL PROCESSING; DATA SETS; ELSEVIER (CO); ENHANCED BIOLOGICAL PHOSPHORUS REMOVAL (EBPR); IN ORDER; INTELLIGENT TOOLS; K MEANS ALGORITHMS; KOHONEN SELF-ORGANIZING MAPS; MULTI DIMENSIONAL DATA SETS; MULTI-DIMENSIONAL DATA; PRINCIPAL COMPONENT ANALYSIS (PCA); PROCESS CONDITIONS; RELEVANT INFORMATION; START UPS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 46149117820     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2007.08.001     Document Type: Article

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