Impact of feature scaling on machine learning models for the diagnosis of diabetes

DU Ozsahin, MT Mustapha, AS Mubarak… - … in Everything (AIE), 2022 - ieeexplore.ieee.org
Due to its high prevalence and incidence, diabetes is considered significant public health.
Since diabetes has no known cure, early diagnosis plays a vital role in effectively managing …

Predicting and analysing the quality of water resources for industrial purposes using integrated data-intelligent algorithms

JC Egbueri - Groundwater for Sustainable Development, 2022 - Elsevier
The continuous increase in the rate of industrialization in developing countries, in recent
times, calls for continuous industrial water quality assessment and prediction. This is to …

Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index

JC Egbueri - Environmental Monitoring and Assessment, 2022 - Springer
Keeping purpose and targeted end-users in perspective, several water quality indices have
been developed over the past decades to summarily convey water quality information to …

Development of integrative data intelligence models for thermo-economic performances prediction of hybrid organic rankine plants

H Tao, OA Alawi, HM Kamar, AA Nafea, MM AL-Ani… - Energy, 2024 - Elsevier
Computer aid models such as machine learning (ML) are massively observed to be
successfully applied in different engineering-related domains. The current research was …

Performances of MLR, RBF-NN, and MLP-NN in the evaluation and prediction of water resources quality for irrigation purposes under two modeling scenarios

JC Egbueri, JC Agbasi - Geocarto International, 2022 - Taylor & Francis
One of the pivotal decision-making tools for sustainable management of water resources for
various uses is accurate prediction of water quality. In the present paper, multiple linear …

An overview of streamflow prediction using random forest algorithm

MM Jibril, A Bello, II Aminu, AS Ibrahim… - GSC Advanced …, 2022 - gsconlinepress.com
Since the first application of Artificial Intelligence in the field of hydrology, there has been a
great deal of interest in exploring aspects of future enhancements to hydrology. This is …

Interpretation the influence of hydrometeorological variables on soil temperature prediction using the potential of deep learning model

S Elsayed, M Gupta… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
The importance of soil temperature (ST) quantification can contribute to diverse ecological
modelling processes as well as for agricultural activities. Over the literature, it was evident …

Feasibility of the Optimal Design of AI-Based Models Integrated with Ensemble Machine Learning Paradigms for Modeling the Yields of Light Olefins in Crude-to …

AG Usman, A Tanimu, SI Abba, S Isik, A Aitani… - ACS …, 2023 - ACS Publications
The prediction of the yields of light olefins in the direct conversion of crude oil to chemicals
requires the development of a robust model that represents the crude-to-chemical …

Genetic neuro-computing model for insights on membrane performance in oily wastewater treatment: An integrated experimental approach

J Usman, SI Abba, NB Ishola, T El-Badawy… - … Research and Design, 2023 - Elsevier
In this study, response surface methodology (RSM) and artificial neural network-based
genetic algorithm (ANN-GA) were utilized to predict two crucial output parameters of …

[PDF][PDF] Comparison of meta-heuristic algorithms for fuzzy modelling of COVID-19 illness' severity classification

NAM Aseri, MA Ismail, AS Fakharudin… - … Journal of Artificial …, 2022 - researchgate.net
The world health organization (WHO) proclaimed the COVID-19, commonly known as the
coronavirus disease 2019, was a pandemic in March 2020. When people are in close …