Prediction of Wastewater Pre-Precipitation Variables Using Self-Organizing Networks

Author

Isaias, Padelis ; Nilsson, Sara ; Stathaki, Anna ; King, Robert E.

Author_Institution

Data & Knowledge Eng. Group, Comput. Res. Inst., Athens

fYear

2005

fDate

27-29 June 2005

Firstpage

932

Lastpage

937

Abstract

This paper describes the derivation and design of an array of self-organizing networks trained by inductive learning for one step ahead prediction of the outputs of the pre-precipitation stage of a wastewater treatment plant with a view to model predictive control of the stage

Keywords

chemical variables control; control system synthesis; learning (artificial intelligence); predictive control; self-adjusting systems; wastewater treatment; inductive learning; one step ahead prediction; predictive control; self-organizing networks; wastewater preprecipitation variable prediction; wastewater treatment plant; Chemicals; Effluents; Instruments; Machine learning; Mathematical model; Neural networks; Predictive control; Predictive models; Self-organizing networks; Wastewater treatment;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation

Conference_Location

Limassol

ISSN

2158-9860

Print_ISBN

0-7803-8936-0

Type

conf

DOI

10.1109/.2005.1467139

Filename

1467139

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3548889