Principal factor analysis for forecasting diurnal water-demand pattern using combined rough-set and fuzzy-clustering technique

Journal of Water Resources Planning and Management

Volumn 139, Issue 1, 2013, Pages 23-33

  Liu, Jing Qing ^a   Cheng, Wei Ping ^a   Zhang, Tu Qiao ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Attribute reduction algorithm; Cumulative weighting coefficient; Diurnal water demand pattern; Fuzzy c mean clustering algorithm; Principal factor analysis

Indexed keywords

DIURNAL WATER-DEMAND PATTERN; DYNAMIC REDUCTION; FUZZY C-MEAN ALGORITHM; FUZZY C-MEAN CLUSTERING ALGORITHM; MATHEMATICAL TOOLS; PRINCIPAL FACTOR ANALYSIS; VARIABLE PRECISION; WEIGHTING COEFFICIENT;

ATMOSPHERIC TEMPERATURE; FACTOR ANALYSIS; FUZZY CLUSTERING; MULTIVARIANT ANALYSIS;

CLUSTERING ALGORITHMS;

AIR TEMPERATURE; ALGORITHM; CLUSTER ANALYSIS; DEMAND ANALYSIS; DIURNAL VARIATION; FACTOR ANALYSIS; FORECASTING METHOD; FUZZY MATHEMATICS; TEMPERATURE EFFECT; WATER DEMAND;

CHINA; HANGZHOU; ZHEJIANG;

EID: 84876698394     PISSN: 07339496     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)WR.1943-5452.0000223     Document Type: Article

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