Development and Implementation of A Neural Fuzzy Operation Support System Available Applied in the Process Control of Environmental Engineering

Artificial neural networks (ANN), which can
learn the historical data of a plant, provide operational
guidance for plant operators, and fuzzy systems (FS)
establish a framework that sets operators' control
experiences into fuzzy rules. In this research, an
interpretation of ANN is provided so that ANN will no
longer be seen as a black-box. This is shown by
establishing the equality between a certain class of
ANN and FS. In addition, an automated knowledge
acquisition procedure is obtained, employing ANN as
a learning machine and a mathematical model from
which to extract fuzzy rules.
For testifying our model purpose, a two-phase
biological treatment system of activated sludge/contact
aeration process was established in this year.