MINIMIZATION OF RISK OF THE ERRONEOUS DECISION IN THE ASSESSMENT OF THE IMPORTANCE OF STATISTICAL RELATIONS OF TECHNICAL AND ECONOMIC INDICATORS OF THE OBJECTS OF ELECTRIC POWER SY... by E. M. Farhadzadeh, A. Z. Muradaliyev, Yu. Z. Farzaliyev, T. K. Rafiyeva, S. A. Abdullayeva

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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. The image is reconstructed using the probabilistic maximum a posteriori estimate. …”
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Beyond the Current Curve: A Novel Curve Warning System Considering Subsequent Curve Speed Limits by N. S. Manikandan, Ganesan Kaliyaperumal

“…Our proposed method, incorporating adjacent curve information, demonstrates significant safety improvements, particularly in reducing the RMSE error when navigating the curves on simulated autonomous vehicles.…”
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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…Deep learning approaches offer significant advantages in capturing high-level representations, thereby improving the accuracy and robustness of edge detection algorithms. …”
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A calibration procedure for simulation models of rural residential buildings using monthly energy bills: A case study in Zhejiang, China by Yuanyuan Wei, Song He, Ping Huang, Yuechen Duan, Bart Julien Dewancker, Luyao Zhou

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Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

“…The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. …”
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YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design by Lu Zhao, Jing Yu

“…In the recognition stage, firstly, the background and sensor thermal noise are used to enhance the classification data set, and the background optimization preprocessing algorithm is designed to improve the adaptability of the model to the complex background. …”
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Multi-Condition Rolling Bearing Fault Denoising Method and Application Based on RIME-VMD by Xin Zhao, Xuebin Liu, Hanshan Li

“…The experimental results show that the RIME-VMD method can effectively remove most of the noise in the rolling bearing fault signal, and the performance evaluation indexes of this method are better than other existing optimization algorithms. …”
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Matching and Control Optimisation of Variable-Geometry Turbochargers for Hydrogen Fuel Cell Systems by Matt L. Smith, Alexander Fritot, Davide Di Blasio, Richard Burke, Tom Fletcher

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An Enhanced Generative Adversarial Network Prediction Model Based on LSTM and Attention for Corrosion Rate in Pipelines by Pujun Long, Mi Liang, Hongjian Chen, Qin Yang

“…This model integrates an improved Generative Adversarial Network with Grey Wolf Optimization and Support Vector Regression (LAGAN-GWO-SVR). …”
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Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

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Evolutionary fuzzy learning for Chinese medicine liver syndrome differentiation by Jia-Yu Yan, Peng-Wei Zhang, Wei-Guo Sheng, Jun-Ping Shi, Wei Ni, Li Li, Yu-Jun Zheng

“…To determine the most appropriate fuzzy membership functions of the fuzzy learning machines, an evolutionary algorithm was employed to optimize the types and parameters of the fuzzy functions simultaneously. …”
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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

“…These findings offer valuable insights and a robust foundation for optimizing design and improving production management in mechanized mining operations.…”
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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

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Intelligent decision-making and regulation method of gas extraction “borehole-pipe network” system by Kai WANG, Dongxu WANG, Aitao ZHOU, Junwen ZHANG, Fangzhou SONG, Chang’ang DU, Yushuang HAO, Xihui FAN, Wei ZHAO

“…Based on the improved particle swarm optimization algorithm, the intelligent optimization decision-making and regulation model of pipeline network is constructed. …”
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Enhancing Three-Dimensional Reconstruction Through Intelligent Colormap Selection by Alexandros Vrochidis, Dimitrios Tzovaras, Stelios Krinidis

“…Experimental results show that image enhancement can lead to a 7.91% and 11.4% improvement, and the enhancement fusion with colormaps improves reconstruction accuracy by 10.82% and 64.11%. …”
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EEG-Based Sleep Stage Classification via Neural Architecture Search by Gangwei Kong, Chang Li, Hu Peng, Zhihui Han, Heyuan Qiao

“…With the improvement of quality of life, people are more and more concerned about the quality of sleep. …”
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Dynamic Adaptive Environmental Flows (DAE‐Flows) to Reconcile Long‐Term Ecosystem Demands With Hydropower Objectives by Ana Paula Dalcin, Guilherme Fernandes Marques, Amaury Tilmant, Marcelo Olivares

“…Even under a drier climate change scenario, this allowed maintenance and improvement of environmental performance in most years, so during severe droughts the water could still be reallocated to hydropower but at a lesser cost to the environment.…”
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Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE by Muhammad Sarmad Mahmood, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Syed Salman Ahmad Zaidi, Muwaffaq Alqurashi, Hawreen Ahmed, Muhammad Adnan, Abdul Hakim Hotak

“…To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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