Title of article :
Determination of the relationship between sewage odour
and BOD by neural networks
Author/Authors :
Guleda Onkal-Engina، نويسنده , , *، نويسنده , , Ibrahim Demira، نويسنده , , Seref N. Enginb، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2005
Abstract :
Sewage treatment works are one of the major sources that cause atmospheric odour pollution. Due to the increase in
environmental concerns, there is a growing number of complaints on odour nuisance. In order to determine the boundaries of legal
standards, reliable and efficient odour measurement methods need to be defined. An electronic nose was used for the purpose of
characterising sewage odours. Samples collected at different locations of a wastewater treatment plant were classified using an
Artificial Neural Network (ANN) trained with a back-propagation algorithm. Additionally, the same method was used to determine
the relation between sewage sample odours and their related Biochemical Oxygen Demand (BOD) values. The overall results have
indicated that ANNs can be used to classify the sewage samples collected from different locations of a wastewater treatment plant.
Moreover, the electronic nose output could be used as an indicator in monitoring the biochemical activities of wastewaters.
Keywords :
Artificial neural network , e-NOSE , biochemical oxygen demand , Sewage odour , back-propagation
Journal title :
Environmental Modelling and Software
Journal title :
Environmental Modelling and Software