DocumentCode :
3482650
Title :
Development of fuzzy fish pond water quality model
Author :
Hidayah, S.N. ; Tahir, NooritawatiMd ; Rusop, M. ; Shah, R.M.S.B.
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA (UiTM), Shah Alam, Malaysia
fYear :
2011
fDate :
5-6 Dec. 2011
Firstpage :
556
Lastpage :
561
Abstract :
Significant water quality assessment method in water system is vital in an environmental management. Various classification techniques have been implemented as part of water quality prediction in aquaculture. However, inconsistency repeatedly arises from haziness of water maintenance-operation; different standard in water criteria leverageas well as decisionentrenched in the decision making output values. Conventional Water Quality Index (WQI) confronted difficulties regarding imprecision when water quality conditions are incorporated with regard to numerous elements, traits, nutrients, and hazardous potentials. Hence, this paper presented a study in water quality assessment for fish pond associating fuzzy logic system and conventional method. The model is based on observation made from commercial fish pond located in Sungai Besar. Initial findings proven that the proposed fuzzy inference system (FIS) are capable and successfully complement divergences and complex circumstances. In future, the proposed pond water quality model can be prolonged to define thenon-regulated contaminants in water.
Keywords :
aquaculture; contamination; environmental management; fuzzy logic; fuzzy reasoning; water pollution; water quality; Malaysia; Sungai Besar; aquaculture; commercial fish pond; decision making output value; environmental management; fuzzy fish pond water quality model; fuzzy inference system; fuzzy logic system; hazardous potential; nonregulated contaminants; nutrients; water criteria; water maintenance-operation; water quality assessment method; water quality index; water system; Chemicals; Fuzzy logic; Indexes; Marine animals; Water conservation; Water pollution; Water resources; Water quality; contaminants; fuzzy inference system; fuzzy logic; water quality index;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Humanities, Science and Engineering (CHUSER), 2011 IEEE Colloquium on
Conference_Location :
Penang
Print_ISBN :
978-1-4673-0021-6
Type :
conf
DOI :
10.1109/CHUSER.2011.6163795
Filename :
6163795
Link To Document :
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