3 citations · 6 across the 10 of their papers we have counts for
4 papers · 1 filter
Smart Ensemble Learning Framework for Predicting Groundwater Heavy Metal Pollution
T. Ansah-Narh, G. Y. Afrifa, J. B. Tandoh +6
Groundwater in the Densu Basin is increasingly threatened by heavy metal contamination, but conventional methods fail to capture the statistical complexity and spatial heterogeneit…
Anomaly Detection in Soil Heavy Metal Contamination Using Unsupervised Learning for Environmental Risk Assessment
Isaac Tettey Adjokatse, Samuel Senyo Koranteng, George Yamoah Afrifa +6
Soil contamination by heavy metals poses a persistent environmental and public health concern in rapidly urbanising regions of Ghana, particularly at unregulated waste disposal sit…
Label Assisted Autoencoder for Anomaly Detection in Power Generation Plants
Marcellin Atemkeng, Victor Osanyindoro, Rockefeller Rockefeller +5
One of the critical factors that drive the economic development of a country and guarantee the sustainability of its industries is the constant availability of electricity. This is…
Predicting Fuel Consumption in Power Generation Plants using Machine Learning and Neural Networks
Gabin Maxime Nguegnang, Marcellin Atemkeng, Theophilus Ansah-Narh +2
The instability of power generation from national grids has led industries (e.g., telecommunication) to rely on plant generators to run their businesses. However, these secondary g…