A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method leverages the advantages of multiple machine-learning algorithms, demonstrating strong operability and improving the accuracy of CBM dynamic predictions. …”
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Lightweight Indoor Positioning System Based on Multiple Self-Learning Features and Key Frame Classification by C. Wang, K. Bi, B. Zhao, M. Li, Y. Chen, S. Tao, J. Yang

“…It has significant optimizations compared with conventional visual solutions in terms of preprocessing data collection, algorithm performance consumption, and versatility.…”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…This article provides a critical analysis of the following cutting-edge methods: DTC with Space Vector Modulation (DTC-SVM), DTC based on Fuzzy Logic (DTC-FL), DTC using Artificial Neural Networks (DTC-ANN), DTC optimized by Genetic Algorithms (DTC-GA), DTC with Ant Colony Optimization (DTC-ACO), DTC with rooted tree optimization (DTC-RTO), Sliding Mode Control (DTC-SMC), and Predictive DTC (P-DTC). …”
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Reinforcement learning applications in water resource management: a systematic literature review by Linus Kåge, Vlatko Milić, Vlatko Milić, Maria Andersson, Magnus Wallén

“…Among the algorithms, deep Q-networks are the most commonly employed. …”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…A Random Forest model is then trained to accurately predict the resource needs of each cluster, enabling optimal allocation. Simulation results show that the proposed approach improves prediction accuracy to 94%, reduces energy consumption by 20%, and decreases response time by 10% compared to existing methods. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…The proposed model achieved an accuracy of 90.39%, with DenseNet201 producing the most accurate results. This AI-driven helmet detection model demonstrates significant potential in improving occupational safety by assisting safety officers, especially in confined environments, reducing human error, and enhancing efficiency.…”
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Efficient Material Flow and Storage Space Determination in Automated Distribution Centers by Mohammed Alnahhal, Nikola Gjeldum, Mohammed Ruzayqat

“…Items with relatively large demand levels have scenario 3 as the optimal one. Results also showed that the model reduces both total costs and stacker crane utilization while improving system flexibility.…”
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Educational frontiers with ChatGPT: a social network analysis of influential tweets by Mehmet Firat, Saniye Kuleli

“… The unprecedented adoption of OpenAI's ChatGPT, marked by reaching 100 million daily users in early 2023, highlights the growing interest in AI for educational improvement. This research aims to analyze the initial public reception and educational impacts of ChatGPT, using social network analysis of the 100 most influential tweets. …”
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Elastic regularization networks for enhanced UAV visual tracking by Qingjiao Meng, Ji Li, Yan Jin, Zhaotian Deng

“…On the DTB70 dataset, the proposed method achieves a precision of 0.747 and a success rate of 0.789, representing improvements of 1% and 2.9%, respectively, over the STRCF algorithm. …”
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RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation by Marco La Salandra, Rosa Colacicco, Simone Panza, Giovanni Fumai, Pierfrancesco Dellino, Domenico Capolongo

“…Unlike existing methods that rely on post-processing, RivAIr is purpose-built for real-time field deployment in data-scarce or emergency scenarios.RivAIr integrates YOLOv8 with an optimized Farneback dense optical flow algorithm focused on water bodies, improving motion estimation accuracy while reducing runtime for real-time UAV processing. …”
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Development and application of an early prediction model for risk of bloodstream infection based on real-world study by Xiefei Hu, Shenshen Zhi, Yang Li, Yuming Cheng, Haiping Fan, Haorong Li, Zihao Meng, Jiaxin Xie, Shu Tang, Wei Li

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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…For example, AI-based support systems offer data-driven insights that improve diagnostic accuracy and patient outcomes thus transforming healthcare delivery 3. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…This tool can support engineers and material designers in developing sustainable RM mixes with improved performance and reduced reliance on extensive laboratory testing.…”
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Integrating cyber-physical systems with embedding technology for controlling autonomous vehicle driving by Manal Abdullah Alohali, Hamed Alqahtani, Abdulbasit Darem, Monir Abdullah, Yunyoung Nam, Mohamed Abouhawwash

“…The study acknowledges the technological limitations of automobile CPSs and investigates hardware acceleration as a potential remedy in addition to algorithmic enhancements. Because of their post-manufacturing adaptability, parallel processing capabilities, and reconfigurability, field programmable gate arrays (FPGAs) are used to execute reinforcement learning in real-time. …”
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Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…Based on the Aras Gray technique, regions 5, 8, and 10 were identified as the most optimal choices, while regions 6 and 9 were deemed less ideal. …”
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Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. Furthermore, model stacking and average ensemble learning methods were adopted to further improve the generalization performance of the model. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…More research is needed to quantitatively examine different contribution of sample sizes, modeling algorithms, variables from different sources, and stratification factors on modeling results, so that we can design an optimal procedure for GSV modeling using airborne Lidar data.…”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The precise prediction of wind power is essential not only for the smooth integration into the power grid but also for the optimization of unit commitment, maintenance scheduling, and the improvement of power traders' profitability. …”
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Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

“…The models were trained and assessed using public datasets and the most effective algorithm was integrated into a mobile application for practical use. …”
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