Intelligent sequence planning for wastewater treatment systems

摘要

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.