Artificial neural network in gaseous emissions prediction with bioreactor usage

Authors:
Piotr Boniecki;Jacek Dach;Krzysztof Pilarski;Aleksander Jȩdruś;Krzysztof Nowakowski;Hanna Piekarska-Boniecka;Jacek Przybył
Affiliations:
Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland;Poznan University of Life Sciences, Poznan, Poland
Venue:
BICA'12 Proceedings of the 5th WSEAS congress on Applied Computing conference, and Proceedings of the 1st international conference on Biologically Inspired Computation
Year:
2012

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Abstract

The artificial neural network is used more and more often for prediction of processes related with the biowaste management. In this area, composting is one of the most important process of biowaste recycling. However, the gaseous emissions from the composted waste are hard to estimate in natural conditions. That is why the usage of laboratory scale bioreactors let to obtain valuable data which is indispensable for neural modelling. Based on this data, neural simulation models enable, in cheap and quick way, to effectively support the cognitive process in order to estimate the complicated, biological phenomena.