title: Decision algorithm based on data mining for coagulant type and dosage in water treatment systems.
abstract: Water shortages are gradually accelerating because higher standards of living are required and water resources are more heavily utilised. Therefore, effective water treatment is necessary in order to retain the required quality and amount of water. General treatment includes coagulation, flocculation, filtering and disinfection. Coagulation, flocculation and disinfection are major components of water treatment processes. In this paper, a new automatic decision algorithm is proposed for coagulation. The proposed method shows how to determine the coagulant type and amount using data mining techniques.
authors.affiliation: School of Electrical and Computer Engineering, Pusan National University, Busan 609-735, South Korea. baehyeon@pusan.ac.kr
authors.forename: H
authors.initials: H
authors.lastname: Bae
authors.forename: S
authors.initials: S
authors.lastname: Kim
authors.forename: Y J
authors.initials: YJ
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D000536:Aluminum Hydroxide / Q000737:chemistry; D003663:Decision Trees; D005427:Flocculation; D016571:Neural Networks, Computer; D017640:Silicates / Q000737:chemistry; D013431:Sulfates / Q000737:chemistry; D018508:Water Purification / Q000379:methods*
chemical_list: D017640:Silicates; D013431:Sulfates; C016213:aluminum oxychloride; D000536:Aluminum Hydroxide