Wilson / In Artificial Neuronal Networks / Artificial Neural Networks / Eng L. P. / USM / Alam Sekitar Malaysia Sdn. / Hall Ltd. / Komatsu / /
Country
Malaysia / Australia / / /
Event
Environmental Issue / /
Facility
pH Temp Salinity Turbidity DS NO3 PO4 E.coli Station / University of Adelaide / /
IndustryTerm
artificial neuronal networks / chemical and biological time-series data / neural networks / data mining / natural rubber processing factories / chemical and biological conditions / unsupervised learning algorithms / /
NaturalFeature
Air Itam River / Air Terjun river / Terjun river / Pinang River / Penang Island / Malaysian Rivers / River Air Itam / Sungai Pinang river / Air river / Dondang river / Jelutong river / /
Organization
University of Adelaide / Congress / School of Distance Education / School of Industrial Technology / Department of Environment / Universiti Sains Malaysia / Department of Irrigation / School of Mathematical Sciences / Several Malaysian government / / /
ProvinceOrState
South Carolina / Penang / /
PublishedMedium
Environmental Research / /
Technology
Neural Network / training algorithm / data mining / machine learning / unsupervised learning algorithms / Pollution Control / /
Predicting Biochemical Oxygen Demand as indicator of river pollution using artificial neural networks