Advanced machine learning technique for solving elliptic partial differential equations using Legendre spectral neural networks by Ishtiaq Ali

“…In this work, a novel approach based on a single-layer machine learning Legendre spectral neural network (LSNN) method is used to solve an elliptic partial differential equation. …”
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Unveiling the Spatial Heterogeneity of Urban Vitality Using Machine Learning Methods: A Case Study of Tianjin, China by Fengshuo Sun, Enxu Wang

“…Residential zones demonstrated higher nighttime UV than daytime UV on weekdays, with the opposite pattern observed on weekends. Public service zones maintained a comparable level of UV between the daytime and nighttime on weekdays. …”
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FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING HOLT WINTER'S EXPONENTIAL SMOOTHING METHOD AND EXTREME LEARNING MACHINE METHOD by Rochdi Wasono, Yulia Fitri, M. Al Haris

“…The Holt Winters Exponential Smoothing method is used because it aligns with the data pattern that includes trends and seasonality in the research, and it has a low level of accuracy. …”
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Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis by Lei Li, Hui Jing, Yuqi Zhao, Shenghua Wu, Boyu Zhu

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The machine psychology of cooperation: can GPT models operationalize prompts for altruism, cooperation, competitiveness, and selfishness in economic games? by Steve Phelps, Yvan I Russell

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Source Analysis of Ozone Pollution in Liaoyuan City’s Atmosphere Based on Machine Learning Models and HYSPLIT Clustering Method by Xinyu Zou, Xinlong Li, Dali Wang, Ju Wang

“…The results indicate that O₃ pollution in Liaoyuan exhibits a distinct seasonal pattern, with the highest concentrations found in spring and summer, peaking in the afternoon. …”
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Non-Invasive Fatigue Detection and Human–Machine Interaction Using LSTM and Multimodal AI: A Case Study by Muon Ha, Yulia Shichkina, Xuan-Hien Nguyen

“…The system analyzes eye blink patterns and facial expression changes captured through a webcam, achieving an accuracy of 92.35% on the UTA-RLDD dataset. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Seasonal wind speed analysis revealed distinct patterns, with winter emerging as the most efficient season for wind, featuring a median wind speed of 7.96 m/s. …”
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Comprehensive Framework for Leak Detection in Water Distribution Systems: A Vibration Signal Processing and Machine LEARNING Approach by Hayder Wthaij, Ajeel Al Ghasheem

“…These features enable capturing the specific vibration patterns of diverse leaks, ‎allowing for accurate identification. …”
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A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection by Han Zhuoxi

“…The UNSW-NB15 dataset, which includes various attack types and normal traffic patterns, is used to evaluate the performance of these two models. …”
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Creating a diagnostic assessment model for autism spectrum disorder by differentiating lexicogrammatical choices through machine learning. by Sumi Kato, Kazuaki Hanawa, Manabu Saito, Kazuhiko Nakamura

“…This approach suggests the possibility of using natural language processing to detect distinctive linguistic patterns in AS, aiming to enhance diagnostic accuracy for differentiating AS from non-AS in adolescents and adults.…”
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A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES Penetrations by João Passagem dos Santos, Hugo Algarvio

“…Specifically, the methodology incorporates neural networks, such as Long Short-Term Memory (LSTM) or Convolutional neural network (CNN) models, to improve forecasting accuracy by capturing temporal dependencies and nonlinear patterns in the data. This study uses operational open data from the Spanish operator from 2014 to 2023 for training. …”
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Support Vector and Linear Regression Machine Learning Model on Amperometric Signals to Predict Glucose Concentration and Hematocrit Volume by Kirti Sharma, Pawan K. Tiwari, Sanjay Kumar Sinha

“…The emergence of advanced machine learning tools and techniques, subsequent to a substantial evolution in data mining strategies, has bestowed the capacity to glean insights and discern concealed patterns from vast datasets, thus enabling extensive analytical pursuits. …”
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MediaWatchers4Climate: Assessing the Accuracy of Climate Change Narratives in Greek Media Through Machine Learning by Thomai Baltzi, Stella Nikitaki, Fani Galatsopoulou, Ioanna Kostarella, Andreas Veglis, Vasilis Vasilopoulos, Dimitris Papaevagelou, Antonis Skamnakis

“…This study introduces MediaWatchers4Climate, a methodological framework that leverages machine learning to evaluate the accuracy and rhetorical framing of climate change narratives in Greek online media. …”
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Integrating Machine Learning and Digital Twins for Enhanced Smart Building Operation and Energy Management: A Systematic Review by Bruno Palley, João Poças Martins, Hermano Bernardo, Rosaldo Rossetti

“…Artificial Intelligence has recently expanded across various applications. Machine Learning, a subset of Artificial Intelligence, is a powerful technique for identifying patterns in data to support decision making and managing the increasing volume of information. …”
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An optical brain-machine interface reveals a causal role of posterior parietal cortex in goal-directed navigation by Ethan Sorrell, Daniel E. Wilson, Michael E. Rule, Helen Yang, Fulvio Forni, Christopher D. Harvey, Timothy O’Leary

“…No learning or adaptation is observed during BMI, indicating that naturally occurring PPC activity patterns are sufficient to drive navigational trajectories in real time. …”
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ReactorNet based on machine learning framework to identify control rod position for real time monitoring in PWRs by Ahmed Omar, Mohamed K. Elhadad, Moamen G. El-Samrah, Tarek F. Nagla, Tamer Mekkawy

“…Abstract This paper presents a novel approach, ReactorNet, a machine learning framework leveraging thermal neutron flux imaging to enable real-time monitoring of pressurized water reactors (PWRs). …”
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Reservoir Inflow Prediction under GCM Scenario Downscaled by Wavelet Transform and Support Vector Machine Hybrid Models by Gusfan Halik, Nadjadji Anwar, Budi Santosa, Edijatno

“…Climate change has significant impacts on changing precipitation patterns causing the variation of the reservoir inflow. …”
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Multi-HM: A Chinese Multimodal Dataset and Fusion Framework for Emotion Recognition in Human–Machine Dialogue Systems by Yao Fu, Qiong Liu, Qing Song, Pengzhou Zhang, Gongdong Liao

“…While existing models show potential for HCI applications, current conversational datasets exhibit critical limitations in real-world deployment, particularly in capturing domain-specific emotional dynamics and context-sensitive behavioral patterns—constraints that hinder semantic comprehension and adaptive capabilities in task-driven HCI scenarios. …”
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Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East by Younes Khosravi, Taha B.M.J. Ouarda, Saeid Homayouni

“…Abstract Climate change in the Middle East has intensified with rising temperatures, shifting rainfall patterns, and more frequent extreme events. This study introduces the Stacking-EML framework, which merges five machine learning models three meta-learners to predict maximum temperature, minimum temperature, and precipitation using CMIP6 data under SSP1-2.6, SSP2-4.5, and SSP5-8.5. …”
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