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Department of MathematicsPhysical Sciences

Hoese Michel Tornyeviadzi

15 Publications5 Research Themes12 Open Access
KNUST Profile
Research Overview & Focus

The researcher's work integrates diverse areas of physical sciences through AI, focusing on optimizing water systems for leakage detection and vulnerability assessment, employing advanced models like deep learning for hydrological forecasting and simulation. Additionally, they explore anaerobic digestion and biogas production for environmental impacts, while also ensuring robust quality monitoring techniques in water treatment plants.

Key Research Themes (5)
Physical Sciences

Anaerobic Digestion and Biogas Production

Physical Sciences

Energy and Environment Impacts

Physical Sciences

Hydrological Forecasting Using AI

Physical Sciences

Water Quality Monitoring Technologies

Physical Sciences

Water Systems and Optimization

Publications (15)

A Machine Learning Approach to Predicting the Turbidity from Filters in a Water Treatment Plant

Open Access
2025Water Quality Monitoring TechnologiesDOI: 10.3390/w17202938

Node search space reduction for optimal placement of pressure sensors in water distribution networks for leakage detection

Open Access
2024Water Systems and OptimizationDOI: 10.1016/j.aej.2024.03.037

Semi-supervised anomaly detection methods for leakage identification in water distribution networks: A comparative study

Open Access
2023Water Systems and OptimizationDOI: 10.1016/j.mlwa.2023.100501

Robust night flow analysis in water distribution networks: A BiLSTM deep autoencoder approach

Open Access
2023Water Systems and OptimizationDOI: 10.1016/j.aei.2023.102135

Leakage detection in water distribution networks via 1D CNN deep autoencoder for multivariate SCADA data

Open Access
2023Water Systems and OptimizationDOI: 10.1016/j.engappai.2023.106062

Dynamic segment criticality analysis: A precursor to scheduling of maintenance routines in water distribution networks

Open Access
2022Water Systems and OptimizationDOI: 10.1016/j.aej.2022.03.012

Emulating process-based water quality modelling in water source reservoirs using machine learning

Open Access
2022Hydrological Forecasting Using AIDOI: 10.1016/j.jhydrol.2022.127675

Predicting Discharges in Sewer Pipes Using an Integrated Long Short-Term Memory and Entropy A-TOPSIS Modeling Framework

Open Access
2022Hydrological Forecasting Using AIDOI: 10.3390/w14030300

A systematic framework for dynamic nodal vulnerability assessment of water distribution networks based on multilayer networks

Open Access
2021Water Systems and OptimizationDOI: 10.1016/j.ress.2021.108217

Modelling the performance potential of forced and natural-draft biomass cookstoves using a hybrid Entropy-TOPSIS approach

2021Energy and Environment ImpactsDOI: 10.1016/j.biombioe.2021.106106

Nodal vulnerability assessment of water distribution networks: An integrated Fuzzy AHP-TOPSIS approach

Open Access
2021Water Systems and OptimizationDOI: 10.1016/j.ijcip.2021.100434

Modelling the impact of weather parameters on the microbial quality of water in distribution systems

2021Water Systems and OptimizationDOI: 10.1016/j.jenvman.2021.111997

Modelling the impact of water temperature, pipe, and hydraulic conditions on water quality in water distribution networks

Open Access
2021Water Systems and OptimizationDOI: 10.2166/wpt.2021.002

Geometry, kinetics and reactor network synthesis: Attainable limits for minimizing residence time in biomethane digesters

2020Anaerobic Digestion and Biogas ProductionDOI: 10.1016/j.compchemeng.2020.106816

Self-optimizing attainable regions of the anaerobic treatment process: Modeling performance targets under kinetic uncertainty

Open Access
2019Anaerobic Digestion and Biogas ProductionDOI: 10.1016/j.watres.2019.115377
Academic Metrics
DepartmentDepartment of Mathematics
Total Publications15
Research Themes5
Open Access Papers12

Department of Mathematics

Kwame Nkrumah University of Science and Technology

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