Blar i Institutt for IKT og realfag på forfatter "Seidu, Razak"
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A Tensor Model for Quality Analysis in Industrial Drinking Water Supply System
Wu, Di; Wang, Hao; Seidu, Razak (Chapter, 2019)Drinking Water Supply (DWS) is one of the most critical and sensitive systems to maintain city operations globally. In Europe, the contradiction between the fast growth of population and obsolete urban water supply ... -
Applying hyperparameter optimization and other model adaption methods to tune existing models for microbial pathogens in drinking water supplies
Noem, Niklas (Master thesis, 2018)The collection and analysis of data on the concentration of pathogenic organisms in raw water sources is critical for the optimization of disinfection processes in water treatment plants. Nevertheless, there are no robust ... -
Comparative predictive modelling of the occurrence of faecal indicator bacteria in a drinking water source in Norway
Mohammed, Hadi; Hameed, Ibrahim A.; Seidu, Razak (Journal article; Peer reviewed, 2018)Presently, concentrations of fecal indicator bacteria (FIB) in raw water sources are not known before water undergoes treatment, since analysis takes approximately 24 h to produce results. Using data on water quality and ... -
Comparison of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gaussian Process for Machine Learning (GPML) Algorithms for the Prediction of Norovirus Concentration in Drinking Water Supply
Mohammed, Hadi; Hameed, Ibrahim A.; Seidu, Razak (Chapter, 2017)Monitoring of Norovirus in drinking water supply is a complicated, rather expensive, process. Norovirus represent a leading cause of acute gastroenteritis in most developed countries. Modeling of general microbial occurrence ... -
Detection of Water Safety Conditions in Distribution Systems Based on Artificial Neural Network and Support Vector Machine
Mohammed, Hadi; Hameed, Ibrahim A.; Seidu, Razak (Peer reviewed; Journal article, 2019)This study presents the development of artificial neural network (ANN) and support vector machine (SVM) classification models for predicting the safety conditions of water in distribution pipes. The study was based on 504 ... -
Quality Risk Analysis for Sustainable Smart Water Supply Using Data Perception
Wu, Di; Wang, Hao; Mohammed, Hadi; Seidu, Razak (Journal article; Peer reviewed, 2019)Constructing Sustainable Smart Water Supply systems are facing serious challenges all around the world with fast expansion of modern cities. Water quality is influencing our life ubiquitously. Traditional urban water quality ... -
Smart data driven quality prediction for urban water source management
Wu, Di; Wang, Hao; Seidu, Razak (Journal article; Peer reviewed, 2020)A water supply system that integrates water source management, treatment and distribution is a critical infrastructure in urban areas. Traditional water quality research mostly focused on separate aspects, lacking a ...