Razak Seidu
Forskning
Publikasjoner
2019
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2019)
Detection of Water Safety Conditions in Distribution Systems Based on Artificial Neural Network and Support Vector Machine.
Advances in Intelligent Systems and Computing
Vitenskapelig artikkel
-
Mohammed, Hadi;
Seidu, Razak.
(2019)
Climate-driven QMRA model for selected water supply systems in Norway accounting for raw water sources and treatment processes.
Science of the Total Environment
Vitenskapelig artikkel
2018
-
Seidu, Razak;
Longva, Andreas.
(2018)
Wastewater Management in Ålesund Kommune:
Status, performance,impacts and suggested secondary wastewater treatment processes.
NTNU
Forskerlinjeoppgave
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2018)
Comparative predictive modelling of the occurrence of faecal indicator bacteria in a drinking water source in Norway.
Science of the Total Environment
Vitenskapelig artikkel
-
Amoah Dennis, Isaac;
Reddy, Poovendhery;
Seidu, Razak;
Stenstrom, Thor Axel.
(2018)
Concentration of soil-transmitted helminth eggs in sludge from South Africa and Senegal: A probabilistic estimation of infection risks associated with agricultural application.
Journal of Environmental Management (JEM)
Vitenskapelig artikkel
-
Dennis Amoah, Isaac;
Reddy, Poovendhery;
Seidu, Razak;
Stenstrom, Thor Axel.
(2018)
Removal of helminth eggs by centralized and decentralized wastewater treatment plants in South Africa and Lesotho: health implications for direct and indirect exposure to the effluents.
Environmental Science and Pollution Research
Vitenskapelig artikkel
-
Mohammed, Hadi;
Longva, Andreas;
Seidu, Razak.
(2018)
Predictive analysis of microbial water quality using machine-learning algorithms.
Aplinkos tyrimai, inzinerija ir vadyba
Vitenskapelig artikkel
2017
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
Adaptive neuro-fuzzy inference system for predicting norovirus in drinking water supply.
IEEE Press
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
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.
Springer
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
Random forest tree for predicting fecal indicator organisms in drinking water supply.
IEEE Press
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
2016
-
Andersson, K;
Rosemarin, A;
Kvarnström, Elisabeth;
McConville, E;
Seidu, Razak;
Dickin, S.
(2016)
Sanitation, Wastewater Management and Sustainability: from Waste Disposal to Resource Recovery.
United Nations Environmental Programme/SEI
Populærvitenskapelig bok
2015
-
Bui Tien, Dieu;
Chuyen, Trung Tran;
Pradhan, Biswajeet;
Revhaug, Inge;
Seidu, Razak.
(2015)
iGeoTrans – a novel iOS application for GPS positioning in geosciences.
Geocarto International
Vitenskapelig artikkel
2014
-
Eregno, Fasil Ejigu;
Grøndahl-Rosado, Ricardo Constante;
Nilsen, Vegard;
Seidu, Razak;
Heistad, Arve;
Myrmel, Mette.
(2014)
Multiple Linear Regression Models for Estimating Microbial Load in a Drinking Water Source: Case from the Glomma River, Norway.
Vann
Vitenskapelig artikkel
-
Eregno, Fasil Ejigu;
Nilsen, Vegard;
Seidu, Razak;
Heistad, Arve.
(2014)
Evaluating the Trend and Extreme Values of Faecal Indicator Organisms in a Raw Water Source: A Potential Approach for Watershed Management and Optimizing Water Treatment Practice.
Environmental Processes
Vitenskapelig artikkel
2013
-
Seidu, Razak.
(2013)
Norwegian drinking water supply systems and risk management: guidelines, directives and microbial risk assessment.
Vann
Vitenskapelig artikkel
2011
-
Stenstrom, Thor Axel;
Seidu, Razak;
Ekane, Nelson;
Zurbrugg, Christian.
(2011)
Microbial exposure and health assessments in sanitation technologies and systems.
Stockholm Environment Institute
Fagbok
2007
-
Seidu, Razak;
Heistad, Arve;
Lindholm, Oddvar;
Vråle, Lasse;
Jenssen, Petter D.;
Stenström, Thor-Axel.
(2007)
Integrating Quantitative Microbial Risk Assessment into Health Risk Management of Water Supply Systems in Norway.
Vann
Vitenskapelig artikkel
Tidsskriftspublikasjoner
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2019)
Detection of Water Safety Conditions in Distribution Systems Based on Artificial Neural Network and Support Vector Machine.
Advances in Intelligent Systems and Computing
Vitenskapelig artikkel
-
Mohammed, Hadi;
Seidu, Razak.
(2019)
Climate-driven QMRA model for selected water supply systems in Norway accounting for raw water sources and treatment processes.
Science of the Total Environment
Vitenskapelig artikkel
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2018)
Comparative predictive modelling of the occurrence of faecal indicator bacteria in a drinking water source in Norway.
Science of the Total Environment
Vitenskapelig artikkel
-
Amoah Dennis, Isaac;
Reddy, Poovendhery;
Seidu, Razak;
Stenstrom, Thor Axel.
(2018)
Concentration of soil-transmitted helminth eggs in sludge from South Africa and Senegal: A probabilistic estimation of infection risks associated with agricultural application.
Journal of Environmental Management (JEM)
Vitenskapelig artikkel
-
Dennis Amoah, Isaac;
Reddy, Poovendhery;
Seidu, Razak;
Stenstrom, Thor Axel.
(2018)
Removal of helminth eggs by centralized and decentralized wastewater treatment plants in South Africa and Lesotho: health implications for direct and indirect exposure to the effluents.
Environmental Science and Pollution Research
Vitenskapelig artikkel
-
Mohammed, Hadi;
Longva, Andreas;
Seidu, Razak.
(2018)
Predictive analysis of microbial water quality using machine-learning algorithms.
Aplinkos tyrimai, inzinerija ir vadyba
Vitenskapelig artikkel
-
Bui Tien, Dieu;
Chuyen, Trung Tran;
Pradhan, Biswajeet;
Revhaug, Inge;
Seidu, Razak.
(2015)
iGeoTrans – a novel iOS application for GPS positioning in geosciences.
Geocarto International
Vitenskapelig artikkel
-
Eregno, Fasil Ejigu;
Grøndahl-Rosado, Ricardo Constante;
Nilsen, Vegard;
Seidu, Razak;
Heistad, Arve;
Myrmel, Mette.
(2014)
Multiple Linear Regression Models for Estimating Microbial Load in a Drinking Water Source: Case from the Glomma River, Norway.
Vann
Vitenskapelig artikkel
-
Eregno, Fasil Ejigu;
Nilsen, Vegard;
Seidu, Razak;
Heistad, Arve.
(2014)
Evaluating the Trend and Extreme Values of Faecal Indicator Organisms in a Raw Water Source: A Potential Approach for Watershed Management and Optimizing Water Treatment Practice.
Environmental Processes
Vitenskapelig artikkel
-
Seidu, Razak.
(2013)
Norwegian drinking water supply systems and risk management: guidelines, directives and microbial risk assessment.
Vann
Vitenskapelig artikkel
-
Seidu, Razak;
Heistad, Arve;
Lindholm, Oddvar;
Vråle, Lasse;
Jenssen, Petter D.;
Stenström, Thor-Axel.
(2007)
Integrating Quantitative Microbial Risk Assessment into Health Risk Management of Water Supply Systems in Norway.
Vann
Vitenskapelig artikkel
Bøker
-
Andersson, K;
Rosemarin, A;
Kvarnström, Elisabeth;
McConville, E;
Seidu, Razak;
Dickin, S.
(2016)
Sanitation, Wastewater Management and Sustainability: from Waste Disposal to Resource Recovery.
United Nations Environmental Programme/SEI
Populærvitenskapelig bok
-
Stenstrom, Thor Axel;
Seidu, Razak;
Ekane, Nelson;
Zurbrugg, Christian.
(2011)
Microbial exposure and health assessments in sanitation technologies and systems.
Stockholm Environment Institute
Fagbok
Del av bok/rapport
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
Adaptive neuro-fuzzy inference system for predicting norovirus in drinking water supply.
IEEE Press
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
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.
Springer
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Mohammed, Hadi;
Hameed, Ibrahim A.;
Seidu, Razak.
(2017)
Random forest tree for predicting fecal indicator organisms in drinking water supply.
IEEE Press
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Rapport
-
Seidu, Razak;
Longva, Andreas.
(2018)
Wastewater Management in Ålesund Kommune:
Status, performance,impacts and suggested secondary wastewater treatment processes.
NTNU
Forskerlinjeoppgave
Undervisning
Emner
- BYGA2900 - Bacheloroppgave bygg
- IP500020 - Introduksjon til smartvann og miljøteknikk
- BYGA2330 - Modellbasert VA-prosjektering
- IP506821 - Fordypningsprosjekt
- IP500021 - Ledningsteknologi og overvannshåntering
- IP500022 - Renseteknikk
- BYGA1200 - Vann- og miljøteknikk
- BYGA2601 - Studiepoenggivende praksis
- BYGA2226 - Vann og miljøteknikk
- BYGA2225 - VA Ledningsnett og overvannshåndtering
Formidling
2018
-
Populærvitenskapelig foredragMohammed, Hadi; Longva, Andreas; Skulstad, Bjørn; Seidu, Razak. (2018) Climate driven integrated hydrodynamic-QMRA model for predicting infection risks-Ålesund Water Supply as a case study. Nordic Water Association The 11th Nordic Drinking Water Conference , Oslo 2018-06-11 - 2018-06-13
-
PosterMohammed, Hadi; Hameed, Ibrahim A.; Seidu, Razak. (2018) An efficient data-driven water control model based on extreme machine learning. Nordic Water Association The 11th Nordic Drinking Water Conference , Oslo 2018-06-11 - 2018-06-13
-
Populærvitenskapelig foredragMohammed, Hadi; Hameed, Ibrahim A.; Seidu, Razak. (2018) Machine learning – based detection of water contamination in water distribution systems . Genetic and Evolutionary Computation Conference , Tokyo 2018-07-15 - 2018-07-17
2017
-
Faglig foredragMohammed, Hadi; Hameed, Ibrahim; Seidu, Razak. (2017) Adaptive Neuro-Fuzzy Inference System for Predicting Norovirus in Drinking Water Supply. IEEE IEEE International Conference on Informatics, Health & Technology (ICIHT) , Riyadh 2017-02-21 - 2017-02-23
2013
-
Populærvitenskapelig foredragSeidu, Razak. (2013) Risikovurdering, vann og United Nations Economic Commission for Europe(UNECE). Norsk Vannforening Risikovurderinger og vannhygiene , Oslo 2013-01-30 - 2013-01-30