Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state.

A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a sugar factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5-10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power.

Amperometric enzyme electrode for organic peroxides determination prepared from horseradish peroxidase immobilized in poly(vinylferrocenium) film.

Organic peroxides, t-butyl hydroperoxide, 2-butanone peroxide, cumene hydroperoxide and t-butyl peracetate, were determined by an amperometric enzyme electrode. The enzyme electrode was prepared through electrostatic immobilization of horseradish peroxidase (HRP) in a polyvinylferrocenium (PVF) film. A PVF(+)ClO(4)(-) film was coated on a Pt foil at +0.