Estimating Sectoral Pullution Load in Lagos, Nigeria using Data Mining Techniques
Industrial pollution is often considered to be one of the
prime factors contributing to air, water and soil pollution.
Sectoral pollution loads (ton/yr) into different media (i.e.
air, water and land) in Lagos were estimated using
Industrial Pollution Projected System (IPPS). These were
further studied using Artificial neural Networks (ANNs), a
data mining technique that has the ability of detecting and
describing patterns in large data sets with variables that are
non- linearly related. Time Lagged Recurrent Network
(TLRN) appeared as the best Neural Network model
among all the neural networks considered which includes
Multilayer Perceptron (MLP) Network, Generalized Feed
Forward Neural Network (GFNN), Radial Basis Function
(RBF) Network and Recurrent Network (RN). TLRN
modelled the data-sets better than the others in terms of the
mean average error (MAE) (0.14), time (39 s) and linear
correlation coefficient (0.84). The results showed that
Artificial Neural Networks (ANNs) technique (i.e., Time
Lagged Recurrent Network) is also applicable and
effective in environmental assessment study.
Keywords: Artificial Neural Networks (ANNs), Data Mining Techniques, Industrial Pollution Projection System (IPPS), Pollution load, Pollution Intensity
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ABOUT THE AUTHORS
Adesesan. B Adeyemo
is a lecturer at the Computer Science Department, University of Ibadan. His research interests include Data/Text mining, Networking and Internet Computing.
Adebola A Oketola
is a lecturer at the Department of Chemistry University of Ibadan she obtained her Doctoral degree in the year 2007 at the University of Ibadan, she is a member of Chemical society of Nigeria, Waste management society of Nigeria. Her research areas are Environmental modelling, persistent organic pollutant analysis, nanotechnology and chemical sensor
Emmanuel O. Adetula
has a Masters degree in Computer Science from the University of Ibadan (2010); He is a Lecturer at the Federal University Lafia, Nigeria His research interest are Data mining and Artificial intelligence and its applications to other fields.
O Osibanjo
obtained his Doctoral degree in the year 1976 from the University of Birmingham and became a professor in the year 1989. He lectures in the Department of Chemistry University of Ibadan and the Director of Basel convention coordinating centre for the African region. Research interests are Environmental modelling, persistent organic pollutant analysis and e- waste.
Adesesan. B Adeyemo
is a lecturer at the Computer Science Department, University of Ibadan. His research interests include Data/Text mining, Networking and Internet Computing.
Adebola A Oketola
is a lecturer at the Department of Chemistry University of Ibadan she obtained her Doctoral degree in the year 2007 at the University of Ibadan, she is a member of Chemical society of Nigeria, Waste management society of Nigeria. Her research areas are Environmental modelling, persistent organic pollutant analysis, nanotechnology and chemical sensor
Emmanuel O. Adetula
has a Masters degree in Computer Science from the University of Ibadan (2010); He is a Lecturer at the Federal University Lafia, Nigeria His research interest are Data mining and Artificial intelligence and its applications to other fields.
O Osibanjo
obtained his Doctoral degree in the year 1976 from the University of Birmingham and became a professor in the year 1989. He lectures in the Department of Chemistry University of Ibadan and the Director of Basel convention coordinating centre for the African region. Research interests are Environmental modelling, persistent organic pollutant analysis and e- waste.
