Integration of Hybrid Machine Learning and Multi-Objective Optimization for Enhanced Turning Parameters of EN-GJL-250 Cast Iron by Yacine Karmi, Haithem Boumediri, Omar Reffas, Yazid Chetbani, Sabbah Ataya, Rashid Khan, Mohamed Athmane Yallese, Aissa Laouissi

“…Advanced optimization models including improved grey wolf optimizer–deep neural networks (DNN-IGWOs), genetic algorithm–deep neural networks (DNN-GAs), and deep neural network–extended Kalman filters (DNN-EKF) were compared with traditional methods like Support Vector Machines (SVMs), Decision Trees (DTs), and Levenberg–Marquardt (LM). …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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Optimization of heat and mass transfer in chemically radiative nanofluids using Cattaneo-Christov fluxes and advanced machine learning techniques by Shazia Habib, Saleem Nasir, Zeeshan Khan, Abdallah S. Berrouk, Waseem Khan, Saeed Islam

“…This functionality empowers specialists to oversee the progression of optimization, identify convergence patterns, and adjust algorithms to achieve superior results, thereby making a remarkable contribution to heat transfer and fluid dynamics.…”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. …”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage by Yiwen Geng, Qi Liu, Hao Zheng, Shitong Yan

“…Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…However, traditional Gaussian Process Regression (GPR) models are constrained by linear assumptions, while conventional filtering algorithms struggle in noisy environments with low signal-to-noise ratios. …”
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Verifiable secure image retrieval for cloud-assisted IoT environments by GUO Jiaqi, MA Zhi, WANG Wensheng, TIAN Cong, DUAN Zhenhua

“…The proposed scheme improves image retrieval accuracy and security while optimizing computational and storage resources, making it suitable for cloud-assisted IoT environments.…”
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Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method by Ajalawit Chantaveerod, Kampol Woradit, Andrew Seagar, Thunyawat Limpiti

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Finding a New Balance Point: Intelligent Optimization of Multi-Target Cognitive Electronic Reconnaissance Strategy for Unmanned Aerial Vehicles by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Xiang Zhu

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Addressing power quality challenges in hybrid renewable energy systems through STATCOM devices and advanced gray wolf optimization technique by Muhammed F. Alwaeli, Sadjad Galvani, Vahid Talavat

“…This algorithm acts to improve control parameters, thus increasing the system's reliability. …”
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Research on unmanned mining truck path planning based on grey wolf optimization adaptive hybrid A* and artificial potential field by HAN Yanling, LYU Jinke, ZHOU Guofeng, ZHANG Like, ZHANG Yun

“…The proposed method emploied the grey wolf optimization algorithm to adaptively adjust the key parameters of the hybrid A*(HA*) algorithm, achieving a multi-objective balance among path length, smoothness, and planning time. …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Using Beijing as a case study, the gradient boosting regression algorithm yielded a prediction accuracy of 92%. Furthermore, in light of the substantial costs associated with waste recovery route planning and site selection for treatment facilities, this research further devised a location and distribution framework for waste treatment centers based on high-precision predictions of waste production while employing multi-objective evolutionary algorithms (MOEAs) alongside the non-dominated sorting genetic algorithm II (NSGA-II) for optimization. …”
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Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response by Zhichun Yang, Lin Cheng, Huaidong Min, Yang Lei, Yanfeng Yang

“…This study proposes a two-stage distributionally robust optimization (DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES. …”
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Optimized radiofrequency shimming using low-heating B1+-mapping in the presence of deep brain stimulation implants: Proof of concept. by Maryam Arianpouya, Benson Yang, Fred Tam, Clare E McElcheran, Simon J Graham

“…The present work addresses this issue in proof of concept using electromagnetic simulations and experimental PTX MRI. A two-step optimization algorithm is proposed and examined for a cylindrical phantom with an implanted wire to enable 1) robust B1+ mapping with low localized heating; and 2) robust RF shimming PTX with low localized heating and good B1+ homogeneity over a large imaging volume. …”
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Optimal Design of a Sensor Network for Guided Wave-Based Structural Health Monitoring Using Acoustically Coupled Optical Fibers by Rohan Soman, Jee Myung Kim, Alex Boyer, Kara Peters

“…The results show that the optimization does indeed have the potential to improve the quality of SHM while reducing the instrumentation costs significantly.…”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence algorithms efficiently process vast datasets from unmanned aerial vehicles, ground vehicles, and satellites, enabling precise and timely interventions. …”
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Daily reference evapotranspiration prediction in Iran: A machine learning approach with ERA5-land data by Ali Asghar Zolfaghari, Maryam Raeesi, Giuseppe Longo-Minnolo, Simona Consoli, Miles Dyck

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