Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

“…Then, the important challenges in MPC implementation, such as computational complexity reduction and delay compensation, weighting factor selection for multi‐objective cost functions, steady state performance and ripple reduction, parameter variations/model mismatching and achieving extended prediction horizons, are surveyed and most relevant solutions are reviewed. …”
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C3-VQA: Cryogenic Counter-Based Coprocessor for Variational Quantum Algorithms by Yosuke Ueno, Satoshi Imamura, Yuna Tomida, Teruo Tanimoto, Masamitsu Tanaka, Yutaka Tabuchi, Koji Inoue, Hiroshi Nakamura

“…Consequently, the C3-VQA reduces the number of wires, leading to a reduction in the total heat dissipation in the cryostat. …”
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Algorithms for Processing Coronavirus Genomes for the Goals and Objectives of Modern Immunoinformatics, Vaccinomics, and Virology by M. V. Sprindzuk, A. S. Vladyko, L. P. Titov, Lu Zhuozhuang, V. I. Bernik

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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…Concurrently, long short-term memory (LSTM) models have shown considerable promise in enhancing air quality predictions, often outperforming other prediction techniques. …”
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Security in Post-Quantum Era: A Comprehensive Survey on Lattice-Based Algorithms by Hien Nguyen, Samsul Huda, Yasuyuki Nogami, Tuy Tan Nguyen

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Developing a hybrid model for comparative analysis of financial data clustering algorithms by Mojtaba Movahedi, Mahdi Homayounfar, Mehdi Fadaei, Mansour Soufi

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Exploring f(Q) gravity through model-independent reconstruction with genetic algorithms by Redouane El Ouardi, Amine Bouali, Safae Dahmani, Ahmed Errahmani, Taoufik Ouali

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Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…This research highlights the transformative potential of integrating advanced data-driven techniques in educational technology to improve group formation and collaborative learning outcomes, offering empirical insights for educators to enhance online interactions and expand pedagogical understanding.…”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Adopt four different noise reduction algorithms for data noise reduction on the raw data of the monitoring points at the intervals of different risk zones, and combine the time series prediction as well as the deep learning prediction method to get the prediction model for environmental risk zoning based on the environmental risk zoning. …”
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Letter and Person Recognition in Freeform Air-Writing Using Machine Learning Algorithms by Huseyin Kunt, Zeki Yetgin, Furkan Gozukara, Turgay Celik

“…This analysis has potential applications in early childhood education for assessing cognitive and psychomotor skills, as well as in user authentication. …”
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Semi-Supervised Attribute Selection Algorithms for Partially Labeled Multiset-Valued Data by Yuanzi He, Jiali He, Haotian Liu, Zhaowen 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. This experimental research focuses on evaluating existing robust cross-validation variants to address the issues of validating credit default models. …”
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Hybrid metaheuristic optimization for detecting and diagnosing noncommunicable diseases by Saleem Malik, S. Gopal Krishna Patro, Chandrakanta Mahanty, Saravanapriya Kumar, Ayodele Lasisi, Quadri Noorulhasan Naveed, Anjanabhargavi Kulkarni, Abdulrajak Buradi, Addisu Frinjo Emma, Naoufel Kraiem

“…The proposed framework introduces novel hybrid algorithms, including the Hierarchical Genetic Multiple Reduct Selection Algorithm (H-GMRA) and the Customized Function-based Particle Swarm Optimization with Rough Set Theory for NCD Feature Selection (CPSO-RST-NFS). …”
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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting by Valdemar M. Cavalcante Junior, Tiago A. Fernandes, Renato Andrade Freitas, Nayara A. de M. S. Amâncio, Fabricio Bradaschia, Marcelo Cabral Cavalcanti

“…The article explores the relevance of choosing the optimization algorithm to obtain accurate parameter estimates in photovoltaic (PV) systems, with the aim of improving the energy efficiency of solar energy. …”
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Simulation of Two Stands Cold Rolling Mill Process Using Neural Networks and Genetic Algorithms in Combination to Avoid the Chatter Phenomenon by Behzad Bahraminejad, Mehrdad Dehghani, Sayed Ali Mousavi

“…So this model is capable to predict speed of Chatter threshold on rolling process of two stand cold rolling mill with the accuracy less than one percent. …”
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Generation of program trajectories for robotic manipulators of point contact welding in the workspace with obstacles by M. M. Kozhevnikov, O. A. Chumakov, I. E. Ilushin, A. V. Hospad

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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…During the feature selection phase, three metaheuristic algorithms—Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), and Harris Hawk Optimization (HHO)—are applied to filter out irrelevant features and retain significant ones. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…However, machine learning models offer a time-efficient solution for predicting pavement performance. This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. …”
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Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images by Pingli Sun, Chenxia Wang, Min Li, Lanqi Liu

“…In this paper, we describe in detail the principles of the space-time noise reduction filter, propose a 3D-filter algorithm for Gaussian noise, an improved 3D-filter algorithm based on the 3D-BDP (bloom-deep-split) filter for mixed noise, and a filter algorithm for luminance and color noise in low-brightness scenes. …”
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