Abba Sani
Abba Sani
Lecturer of Mathematics, Umaru Musa Yar'adua University Katsina Nigeria
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Cited by
Wastewater treatment plant performance analysis using artificial intelligence–an ensemble approach
V Nourani, G Elkiran, SI Abba
Water Science and Technology 78 (10), 2064-2076, 2018
Flash-flood susceptibility assessment using multi-criteria decision making and machine learning supported by remote sensing and gis techniques
R Costache, QB Pham, E Sharifi, NTT Linh, SI Abba, M Vojtek, ...
Remote Sensing 12 (1), 106, 2020
Multi-step ahead modelling of river water quality parameters using ensemble artificial intelligence-based approach
G Elkiran, V Nourani, SI Abba
Journal of Hydrology 577, 123962, 2019
Artificial intelligence-based approaches for multi-station modelling of dissolve oxygen in river
G Elkiran, V Nourani, SI Abba, J Abdullahi
Global Journal of Environmental Science and Management 4 (4), 439-450, 2018
River water modelling prediction using multi-linear regression, artificial neural network, and adaptive neuro-fuzzy inference system techniques
SI Abba, SJ Hadi, J Abdullahi
Procedia computer science 120, 75-82, 2017
Potential of hybrid data-intelligence algorithms for multi-station modelling of rainfall
QB Pham, SI Abba, AG Usman, NTT Linh, V Gupta, A Malik, R Costache, ...
Water Resources Management 33 (15), 5067-5087, 2019
Effluent prediction of chemical oxygen demand from the astewater treatment plant using artificial neural network application
SI Abba, G Elkiran
Procedia computer science 120, 156-163, 2017
Emerging evolutionary algorithm integrated with kernel principal component analysis for modeling the performance of a water treatment plant
SI Abba, QB Pham, AG Usman, NTT Linh, DS Aliyu, Q Nguyen, QV Bach
Journal of Water Process Engineering 33, 101081, 2020
Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series
B Mohammadi, NTT Linh, QB Pham, AN Ahmed, J Vojtekov, Y Guan, ...
Hydrological Sciences Journal 65 (10), 1738-1751, 2020
Simulation for response surface in the HPLC optimization method development using artificial intelligence models: A data-driven approach
SI Abba, AG Usman, I Selin
Chemometrics and Intelligent Laboratory Systems 201, 104007, 2020
Non-linear input variable selection approach integrated with non-tuned data intelligence model for streamflow pattern simulation
SJ Hadi, SI Abba, SS Sammen, SQ Salih, N Al-Ansari, ZM Yaseen
IEEE Access 7, 141533-141548, 2019
Design and Performance Evaluation of a Low-Cost Autonomous Sensor Interface for a Smart IoT-Based Irrigation Monitoring and Control System
S Abba, J Wadumi Namkusong, JA Lee, M Liz Crespo
Sensors 19 (17), 3643, 2019
Evolutionary computational intelligence algorithm coupled with self-tuning predictive model for water quality index determination
SI Abba, SJ Hadi, SS Sammen, SQ Salih, RA Abdulkadir, QB Pham, ...
Journal of Hydrology 587, 124974, 2020
A novel multi-model data-driven ensemble technique for the prediction of retention factor in HPLC method development
AG Usman, S Işik, SI Abba
Chromatographia 83, 933-945, 2020
An autonomous self-aware and adaptive fault tolerant routing technique for wireless sensor networks
S Abba, JA Lee
Sensors 15 (8), 20316-20354, 2015
A parametric-based performance evaluation and design trade-offs for interconnect architectures using FPGAs for networks-on-chip
S Abba, JA Lee
Microprocessors and Microsystems 38 (5), 375-398, 2014
Estimation of water quality index using artificial intelligence approaches and multi-linear regression
MS Gaya, SI Abba, AM Abdu, AI Tukur, MA Saleh, P Esmaili, NA Wahab
Int J Artif Intell ISSN 2252 (8938), 8938, 2020
Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index
SI Abba, QB Pham, G Saini, NTT Linh, AN Ahmed, M Mohajane, ...
Environmental Science and Pollution Research 27 (33), 41524-41539, 2020
Multi-parametric modeling of water treatment plant using AI-based non-linear ensemble
SI Abba, V Nourani, G Elkiran
Journal of Water Supply: Research and Technology-Aqua 68 (7), 547-561, 2019
Smart framework for environmental pollution monitoring and control system using IoT-based technology
A Sani, PE Beauty
Sens. Transducers 229, 84-93, 2019
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