DocumentCode :
1241610
Title :
Intelligent sequence planning for wastewater treatment systems
Author :
Krovvidy, S. ; Wee, William G. ; Suidan, Makram ; Summers, R. Scott ; Coleman, John J. ; Rossman, Lewis
Author_Institution :
Cincinnati Univ., OH, USA
Volume :
9
Issue :
6
fYear :
1994
Firstpage :
15
Lastpage :
20
Abstract :
The article presents a system for intelligent sequence planning of wastewater treatment systems called Sowat, an approach that uses fuzzy sets to determine the best technologies for different compounds and heuristic search to generate optimal treatment trains. The Sequence Optimizer for Wastewater Treatment (Sowat) solves the wastewater treatment problem in two phases: analysis and synthesis. The system first analyzes the treatability database and develops fuzzy relationships between treatment technologies and waste stream contaminants. It couples these relationships with expert rules (for ordering the technologies in a treatment train), and with pretreatment conditions to be satisfied (for applying the treatment technologies). Then, in the synthesis phase, a heuristic search function uses these relationships to generate treatment trains in order of increasing cost. This phase includes a menu based user interface for performing "what if" analysis.<>
Keywords :
environmental science computing; expert systems; fuzzy set theory; heuristic programming; planning (artificial intelligence); search problems; waste disposal; water supply; water treatment; Sequence Optimizer for Wastewater Treatment; Sowat; expert rules; fuzzy relationships; fuzzy sets; heuristic search; heuristic search function; intelligent sequence planning; menu based user interface; optimal treatment trains; pretreatment conditions; synthesis phase; treatability database; waste stream contaminants; wastewater treatment systems; what if analysis; Cost function; Data analysis; Databases; Fuzzy sets; Fuzzy systems; Intelligent systems; Performance analysis; Technology planning; User interfaces; Wastewater treatment;
fLanguage :
English
Journal_Title :
IEEE Expert
Publisher :
ieee
ISSN :
0885-9000
Type :
jour
DOI :
10.1109/64.363257
Filename :
363257
Link To Document :
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