The classification of EMG signals using machine learning for the construction of a silent speech interface. by Chandrashekhar, V.

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Combining the SHAP Method and Machine Learning Algorithm for Desert Type Extraction and Change Analysis on the Qinghai–Tibetan Plateau by Ruijie Lu, Shulin Liu, Hanchen Duan, Wenping Kang, Ying Zhi

“…In this work, five different machine learning algorithms are used to classify different desert types on the Qinghai–Tibetan Plateau (QTP), and their classification performance is evaluated on the basis of their classification results and classification accuracy. …”
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Urban growth simulation using cellular automata model and machine learning algorithms (case study: Tabriz metropolis) by Omid Ashkriz, Babak Mirbagheri, Ali Akbar Matkan, Alireza Shakiba

“…The purpose of this study was to evaluate the performance accuracy of the proposed machine learning algorithms by spatial cross-validation method in combination with the cellular automata model to simulate urban growth.Material and methods: In this study, to analyze urban land-use changes, Landsat satellite images related to the years 1997, 2006, and 2015 were classified using the support vector machine algorithm. …”
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Mapping Nationwide Subfield Division Dynamics in Saudi Arabia Using Temporal Patterns of Sentinel-2 NDVI and Machine Learning by Ting Li, Oliver Miguel Lopez Valencia, Matthew F. McCabe

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Subject based feature selection for hybrid brain computer interface using genetic algorithm and support vector machine by Nida Mateen, Mehreen Naeem, Muhammad Jawad Khan, Talha Yousaf, Ahsan Ali, Wael A. Altabey, Mohammad Noori, Sallam A Kouritem

“…The framework outperforms traditional filter- and wrapper-based feature selection methods on representative subjects, confirming its robustness and adaptability across individual neural patterns. These results highlight the importance of personalized feature selection in hybrid BCIs and demonstrate the viability of evolutionary algorithms for real-time, low-latency brain–machine applications.…”
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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…To optimize the performance of machine learning models, the paper incorporates genetic algorithms for hyperparameter optimization. …”
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Effect of geographical parameters on PM10 pollution in European landscapes: a machine learning algorithm-based analysis by Seyedehmehrmanzar Sohrab, Nándor Csikós, Péter Szilassi

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Seasonal forecasting of the hourly electricity demand applying machine and deep learning algorithms impact analysis of different factors by Heba-Allah Ibrahim El-Azab, R. A. Swief, Noha H. El-Amary, H. K. Temraz

“…Where the whole database is split into four seasons based on demand patterns. This article’s integrated model is built on techniques for machine and deep learning methods: Adaptive Neural-based Fuzzy Inference System, Long Short-Term Memory, Gated Recurrent Units, and Artificial Neural Networks. …”
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Learning control system of lifting machine motors by V. I. Zimovets, A. S. Chirva, O. I. Marishchenko

“…The main way of increasing the efficiency of the automated control system of lifting machine motors is giving it the properties of adaptability on the basis of ideas and methods of machine learning and pattern recognition. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers by Tanjie Wang, Yueshen Xu, Xinkui Zhao, Zhiping Jiang, Rui Li

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Pattern and semantic analysis to improve unsupervised techniques for opinion target identification by Khairullah khan, Ashraf Ullah, Baharum Baharudin

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Audiogram Digitization Tool for Audiological Reports by Francois Charih, James R. Green

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Algorithms and Methods for Individual Source Camera Identification: A Survey by Jaroslaw Bernacki, Rafal Scherer

“…This paper presents a comprehensive review of the existing methods and algorithms used for this purpose. It discusses approaches based on matrix noise analysis, including methods utilizing sensor pattern noise, photo response non-uniformity, statistical methods, aberrations analysis, as well as modern techniques based on deep neural networks and machine learning. …”
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The LETBP feature descriptor based fish species classification using Kepler optimization with Extreme Learning Machine by Annalakshmi GANESAN, Sakthivel Murugan SANTHANAM

“…The extracted unique feature values are given to the Extreme Learning Machine (ELM) for the final classification. The ELM network randomly selects the bias and weights and in order to overcome this issue an optimization technique called Kepler Optimization Algorithm (KOA) is adopted. …”
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Using Machine Learning to Identify the Dynamic Evolution Patterns of Negative Emotions in Perinatal Women: A Longitudinal Study in Southwest China by Yuan Zhang, Wenlong Li, Jian Zou, Guohui Yang, Xiaoni Zhong, Biao Xie

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Snow Distribution Patterns Revisited: A Physics‐Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub‐Arctic by R. L. Crumley, C. L. Bachand, K. E. Bennett

“…Abstract Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year‐to‐year patterns due to local topographic, weather, and vegetation characteristics. …”
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USING REINFORCEMENT LEARNING ALGORITHMS FOR UAV FLIGHT OPTIMIZATION by O. Dutsiak, V. Yuzevych

“…Machine learning gives UAVs the ability to discern patterns and make predictions based on data, thus bypassing the need for pre-programmed instructions during autonomous flight. …”
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Identification of anoikis-related genes classification patterns and immune infiltration characterization in chronic rhinosinusitis with nasal polyps based on machine learning by Ziqi Chen, Lingmei Qu, Qing Hao, Shuang Teng, Shuo Liu, Qin Wu, Hongtian Yi, Xianji Shen, Liang Li, Zhaonan Xu, Yanan Sun

“…Immune cell infiltration was analysed using the CIBERSORT algorithm. CRSwNP samples were classified via consensus clustering. …”
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Predictors of depression among Chinese college students: a machine learning approach by Lin Luo, Junfeng Yuan, Chenghan Wu, Yanling Wang, Rui Zhu, Huilin Xu, Luqin Zhang, Zhongge Zhang

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