ANN Flexible Forecasting for the Adaptive Monitoring of a Multi-Tube Reactor

Author

Nastac, Iulian ; Cristea, Paul

Author_Institution

Polytech. Univ. of Bucharest, Bucharest

fYear

2007

fDate

27-30 June 2007

Firstpage

193

Lastpage

196

Abstract

The paper presents a flexible artificial neural network (ANN) model, in order to support modifications of a complex input-output function that describes the catalyst monitoring process of a multi-tube reactor. The goal is to obtain a good accuracy of the predicted data by using an optimal ANN architecture and well-suited delay vectors. The research targets the implementation of an adaptive system, which can be periodically retrained, in order to continuously learn the latest evolution of the catalyst process.

Keywords

catalysts; chemical engineering computing; chemical reactors; neural nets; process monitoring; ANN flexible forecasting; adaptive catalyst monitoring process; artificial neural network; complex input-output function; delay vectors; multi tube reactor; Adaptive systems; Artificial neural networks; Delay; Electronic mail; Feeds; Fluid flow measurement; Inductors; Monitoring; Neural networks; Temperature; adaptive forecasting; delay vector; neural network; retraining technique; scaling factor;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Image Processing, 2007 and 6th EURASIP Conference focused on Speech and Image Processing, Multimedia Communications and Services. 14th International Workshop on

Conference_Location

Maribor

Print_ISBN

978-961-248-029-5

Electronic_ISBN

978-961-248-029-5

Type

conf

DOI

10.1109/IWSSIP.2007.4381186

Filename

4381186