Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.
Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.
Comas
J
J
Laboratori d'Enginyeria Química i Ambiental (LEQUiA), Universitat de Girona, Campus Montilivi s/n, E-1 7071 Girona, Catalonia, Spain. quim@lequia.udg.es
Rodríguez-Roda
I
I
Poch
M
M
Gernaey
K V
KV
Rosen
C
C
Jeppsson
U
U
D001185:Artificial Intelligence; D019985:Benchmarking; D019149:Bioreactors; D003198:Computer Simulation; D008954:Models, Biological; D009566:Nitrates / Q000032:analysis; D009584:Nitrogen / Q000302:isolation & purification; D010100:Oxygen / Q000032:analysis; D011891:Rain; D012722:Sewage; D014865:Waste Disposal, Fluid
D009566:Nitrates; D012722:Sewage; D009584:Nitrogen; D010100:Oxygen