Adaptive Nonlinear Proportional–Integral–Derivative Control of a Continuous Stirred Tank Reactor Process Using a Radial Basis Function Neural Network by Joo-Yeon Lee, Gang-Gyoo Jin, Gun-Baek So

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Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models by Paul Arévalo, Dario Benavides, Danny Ochoa-Correa, Alberto Ríos, David Torres, Carlos W. Villanueva-Machado

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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

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Stroke Dataset Modeling: Comparative Study of Machine Learning Classification Methods by Kalina Kitova, Ivan Ivanov, Vincent Hooper

“…Stroke prediction is a vital research area due to its significant implications for public health. …”
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Optimization of Offshore Saline Aquifer CO₂ Storage in Smeaheia Using Surrogate Reservoir Models by Behzad Amiri, Ashkan Jahanbani Ghahfarokhi, Vera Rocca, Cuthbert Shang Wui Ng

“…Machine learning-based Surrogate Reservoir Models (SRMs) can replace/augment multi-physics numerical simulations by replicating the reservoir simulation results with reduced computational effort while maintaining accuracy compared with numerical simulations. This research will demonstrate SRMs’ potential in long-term simulations and optimization of geological carbon storage in a real-world geological setting and address challenges in big data curation and model training. …”
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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

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Comprehensive Risk Assessment of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis by Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. McCann

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Multi-Objective Optimization for Green BTS Site Selection in Telecommunication Networks Using NSGA-II and MOPSO by Salar Babaei, Mehran Khalaj, Mehdi Keramatpour, Ramin Enayati

“…However, the NSGAII algorithm performs better in terms of computational time for medium-sized problems compared to the MOPSO algorithm. …”
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Combination of Conditioning Factors for Generation of Landslide Susceptibility Maps by Extreme Gradient Boosting in Cuenca, Ecuador by Esteban Bravo-López, Tomás Fernández, Chester Sellers, Jorge Delgado-García

“…In this study, a specific Machine Learning (ML) method was further analyzed due to the good results obtained in the previous stage of this research. The algorithm implemented is Extreme Gradient Boosting (XGBoost), which was used to evaluate the susceptibility to landslides recorded in the city of Cuenca (Ecuador) and its surroundings, generating the respective Landslide Susceptibility Maps (LSM). …”
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CSpredR: A Multi-Site mRNA Subcellular Localization Prediction Method Based on Fusion Encoding and Hybrid Neural Networks by Xiao Wang, Wenshuai Suo, Rong Wang

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Machine Learning Reconstruction of Wyrtki Jet Seasonal Variability in the Equatorial Indian Ocean by Dandan Li, Shaojun Zheng, Chenyu Zheng, Lingling Xie, Li Yan

“…To address the scarcity of in situ observational data, this study developed a satellite remote sensing-driven multi-parameter coupled model and reconstructed the WJ’s seasonal variations using the XGBoost machine learning algorithm. The results revealed that wind stress components, sea surface temperature, and wind stress curl serve as the primary drivers of its seasonal dynamics. …”
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Automatic Generation of Synthesisable Hardware Description Language Code of Multi-Sequence Detector Using Grammatical Evolution by Bilal Majeed, Rajkumar Sarma, Ayman Youssef, Douglas Mota Dias, Conor Ryan

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Analysis of Reliability and Efficiency of Information Extraction Using AI-Based Chatbot: The More-for-Less Paradox by Eugene Levner, Boris Kriheli

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Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges by Tomer Raitsis, Yossi Elgazari, Guy E. Toibin, Yotam Lurie, Shlomo Mark, Oded Margalit

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Ultra-Low-Cost Real-Time Precise Point Positioning Using Different Streams for Precise Positioning and Precipitable Water Vapor Retrieval Estimates by Mohamed Abdelazeem, Amgad Abazeed, Hussain A. Kamal, Mudathir O. A. Mohamed

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A VIKOR-Based Sequential Three-Way Classification Ranking Method by Wentao Xu, Jin Qian, Yueyang Wu, Shaowei Yan, Yongting Ni, Guangjin Yang

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Can the Plantar Pressure and Temperature Data Trend Show the Presence of Diabetes? A Comparative Study of a Variety of Machine Learning Techniques by Eduardo A. Gerlein, Francisco Calderón, Martha Zequera-Díaz, Roozbeh Naemi

“…For the experiments, 20 regression models and 16 classification algorithms were employed, and the performance was evaluated using a five-fold cross-validation strategy. …”
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Comparative Analysis of BERT and GPT for Classifying Crisis News with Sudan Conflict as an Example by Yahya Masri, Zifu Wang, Anusha Srirenganathan Malarvizhi, Samir Ahmed, Tayven Stover, David W. S. Wong, Yongyao Jiang, Yun Li, Qian Liu, Mathieu Bere, Daniel Rothbart, Dieter Pfoser, Chaowei Yang

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Unlocking the Potential of Remanufacturing Through Machine Learning and Data-Driven Models—A Survey by Yong Han Kim, Wei Ye, Ritbik Kumar, Finn Bail, Julia Dvorak, Yanchao Tan, Marvin Carl May, Qing Chang, Ragu Athinarayanan, Gisela Lanza, John W. Sutherland, Xingyu Li, Chandra Nath

“…This study embarks on a comprehensive review and in-depth analysis of state-of-the-art algorithms across various facets of remanufacturing processes and operations. …”
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Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU by Jonathan Decker, Vincent Florens Hasse, Julian Kunkel

“…Emulations created through Q8S provide a higher level of detail than simulations and can be used to train machine learning scheduling algorithms. By providing an environment capable of executing real workloads, Q8S enables researchers and developers to test and refine their scheduling algorithms, ultimately leading to more efficient and effective heterogeneous cluster management. …”
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