Machine Learning Algorithm for Assessing Photovoltaic Panels Partial Shading Losses based on Inverter Data by Armando Luís Sousa Araujo, Tiago Francisco Pires

“…These algorithms recognise similarities and patterns using expected and measured power data. …”
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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…Recent studies have emphasized the pervasive utilization of machine learning-based algorithms in the field of electric load forecasting for industrial plants. …”
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A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis by Maad M. Mijwil, Mohammad Aljanabi

“…Machine learning algorithms can scrutinize vast quantities of data from electronic health records, medical images, and other sources to identify patterns and make predictions, which can support healthcare professionals and experts in making better-informed decisions, enhancing patient care, and determining a patient's health status. …”
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A Survey on Machine Learning Enhanced Integrated Sensing and Communication Systems: Architectures, Algorithms, and Applications by Mikael Ade Krisna Respati, Byung Moo Lee

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Machine learning algorithms applied to the diagnosis of COVID-19 based on epidemiological, clinical, and laboratory data by Silvia Elaine Cardozo Macedo, Marina de Borba Oliveira Freire, Oscar Schmitt Kremer, Ricardo Bica Noal, Fabiano Sandrini Moraes, Mauro André Barbosa Cunha

“…Epidemiological, clinical, and laboratory data were processed by machine learning algorithms in order to identify patterns. …”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…This paper analyses the impact of cultural factors on digital marketing strategies in Pakistan. Improvement of machine learning (ML) techniques combined with the Honey Bee Algorithm (HBA) has been incorporated for better solutions. …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

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Exploring high opioid prescriptions among nephrologists in the United States using machine learning algorithms by Shivashankar Basapura Chandrashekarappa, Sulaf Assi, Manoj Jayabalan, Abdullah Al-Hamid, Dhiya Al-Jumeily

“…As these factors are complex in nature, understanding them requires machine learning approach. This study explored overprescribing opioids among nephrologists in the US using unsupervised machine learning algorithms. …”
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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

“…However, traditional drought monitoring approaches are limited in dealing with data imbalances and capturing complex temporal patterns. Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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CIAO: A machine-learning algorithm for mapping Arctic Ocean Chlorophyll-a from space by Maria Laura Zoffoli, Vittorio Brando, Gianluca Volpe, Luis González Vilas, Bede Ffinian Rowe Davies, Robert Frouin, Jaime Pitarch, Simon Oiry, Jing Tan, Simone Colella, Christian Marchese

“…To improve these results, we developed CIAO (Chlorophyll In the Arctic Ocean), a machine learning-based algorithm specifically designed for AO waters and trained with satellite Rrs data. …”
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Spatiotemporal estimation of ambient forest phytoncides: Unveiling patterns through geospatial-based machine learning approach by Aji Kusumaning Asri, Hao-Ting Chang, Chia-Pin Yu, Wan-Yu Liu, Yinq-Rong Chern, Rui-Hao Xie, Shih-Chun Candice Lung, Kai Hsien Chi, Yu-Cheng Chen, Sen-Sung Cheng, Gary Adamkiewicz, John D. Spengler, Chih-Da Wu

“…The results showed that RF and XGB were the most effective algorithms, explaining approximately 83.3% and 98.4% of the spatiotemporal variability in camphene and α-pinene, respectively. …”
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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

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Investigation of Micro-Scale Damage and Weakening Mechanisms in Rocks Induced by Microwave Radiation and Their Associated Strength Reduction Patterns: Employing Meta-Heuristic Opti... by Zhongyuan Gu, Xin Xiong, Chengye Yang, Miaocong Cao

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Application of smart technologies for predicting soil erosion patterns by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid, Shiva Gharibi, Jing-Cheng Han

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A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection by N. K. Sreeja

“…This paper proposes a novel instance-based classification algorithm called Weighted Pattern Matching based Classification (PMC+) for classifying imbalanced data. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

“…The practical part of the study included the development of machine learning algorithms for predicting economic indexes. …”
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Improving the Efficiency of Screen Type Potato Sorting Machines by a Modification of the Sieve Drive Movement Algorithm by A. G. Ivanov, M. N. Erokhin, S. P. Kazantsev, P. V. Dorodov, I. I. Khuzyakhmetov, I. T. Khakimov

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A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset by Rulyansyah Permata Putra, Amarudin Amarudin

“…In today’s digital era, cyberattacks are becoming increasingly complex, rendering traditional rule-based Intrusion Detection Systems (IDS) often ineffective in recognizing new attack patterns. The primary objective of this study is to design and implement a machine learning model for detecting network intrusions efficiently while minimizing latency, through a comparative analysis of several algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and Boosting. …”
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Optimizing a Machine Learning Algorithm by a Novel Metaheuristic Approach: A Case Study in Forecasting by Bahadır Gülsün, Muhammed Resul Aydin

“…This study introduces a novel hybrid approach that combines the artificial bee colony (ABC) and fire hawk optimizer (FHO) algorithms, specifically designed to enhance hyperparameter optimization in machine learning-based forecasting models. …”
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