[HTML][HTML] Evaluating electrical power yield of photovoltaic solar cells with k-Nearest neighbors: A machine learning statistical analysis approach

SS Shijer, AH Jassim, LA Al-Haddad… - e-Prime-Advances in …, 2024 - Elsevier
The increasing demand for sustainable and renewable energy solutions reflects the critical
importance of advancing photovoltaic (PV) technology and its operational efficiency. In …

Enhancing building sustainability through aerodynamic shading devices: an integrated design methodology using finite element analysis and optimized neural …

LA Al-Haddad, YM Al-Muslim, AS Hammood… - Asian Journal of Civil …, 2024 - Springer
In the quest for sustainable building solutions, attention has increasingly turned to innovative
structural designs and technologies that minimize environmental impact. Within this context …

Response to letter to the Editor from Y. Takefuji on “Beyond principal component analysis: Enhancing feature reduction in electronic noses through robust statistical …

Z Zheng, K Liu, Y Zhou, M Debliquy… - Trends in Food Science …, 2025 - Elsevier
Background Principal Component Analysis (PCA) is extensively utilized in Electronic Nose
(E-nose) research for dimensionality reduction, allowing simplification of high-dimensional …

[HTML][HTML] Forecasting sustainable water production in convex tubular solar stills using gradient boosting analysis

WH Alawee, LA Al-Haddad, A Basem, DJ Jasim… - Desalination and Water …, 2024 - Elsevier
Water scarcity is an important global issue that necessitates the development of sufficient
and sustainable desalination technologies. This study forecasts the productivity of two solar …

UAV propeller fault diagnosis using deep learning of non-traditional χ2-selected Taguchi method-tested Lempel–Ziv complexity and Teager–Kaiser energy features

LA Al-Haddad, W Giernacki, A Basem, ZH Khan… - Scientific Reports, 2024 - nature.com
Fault detection and isolation in unmanned aerial vehicle (UAV) propellers are critical for
operational safety and efficiency. Most existing fault diagnosis techniques rely basically on …

Environmental engineering solutions for efficient soil classification in southern Syria: a clustering-correlation extreme learning approach

SA Al-Haddad, LA Al-Haddad, AA Jaber - International Journal of …, 2024 - Springer
The classification of soil types for agricultural management systems and environmental
engineering is extremely important for land use planning and environmental conservation …

[HTML][HTML] Leak detection and localization in water distribution systems using advanced feature analysis and an Artificial Neural Network

NM Mahdi, AH Jassim, SA Abulqasim, A Basem… - Desalination and Water …, 2024 - Elsevier
This study capitalizes on a dataset, originally including 280 sensory measurements from a
laboratory-scale water distribution system, to advance the concept of leakage diagnosis and …

Naïve Bayes algorithm for timely fault diagnosis in helical gear transmissions using vibration signal analysis

AG Abdulameer, AS Hammood… - International Journal on …, 2024 - Springer
Vibration signal analysis assumes a critical role in the diagnosis of faults within helical gear
transmissions, facilitating early detection and mitigation of potential failures. This paper is …

[HTML][HTML] Innovative Machine Learning Approaches for Complexity in Economic Forecasting and SME Growth: A Comprehensive Review

MI Al-Karkhi, G Rza̧dkowski - Journal of Economy and Technology, 2025 - Elsevier
Economic forecasting and small and medium-sized enterprises (SMEs) growth prediction
have become essential tools for guiding policy, business strategy, and economic …

A data fusion analysis and random forest learning for enhanced control and failure diagnosis in rotating machinery

BG Mejbel, SA Sarow, MT Al-Sharify… - Journal of Failure …, 2024 - Springer
In a heavily-subjected-to-failure field of rotating machinery, the need for accurate and
reliable detection methods is paramount. This paper aims to advance fault detection …