Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…Results demonstrate the effectiveness of predictive analytics in improving supply chain quality management, enabling enterprises to proactively reduce defect rates, minimize costs, and optimize return on investment (ROI). …”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Reliable prediction models are crucial for optimizing energy management, ensuring grid stability, and minimizing operational costs. …”
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A New Comprehensive Model to Simulate and Optimize Fluid Flow in Complex Well‐Formation System for In Situ Leaching Uranium by Zhaokun Li, Xuebin Su, Yangquan Jiao, Yu Zhang, Yang Qiu, Xiaodong Hu

“…Furthermore, a hybrid multiobjective optimization algorithm was used to complete the parameter optimization of well‐storage coupling for ISL of uranium. …”
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Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

“…A deep vision-based recognition system, enhanced by an improved YOLOv5 algorithm and multi-feature fusion, was employed for real-time object detection and pose estimation. …”
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Transforming Manufacturing Quality Management with Cognitive Twins: A Data-Driven, Predictive Approach to Real-Time Optimization of Quality by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. …”
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Game-Theory-Based Multi-Objective Optimization for Enhancing Environmental and Social Life Cycle Assessment in Steel–Concrete Composite Bridges by David Martínez-Muñoz, Jose V. Martí, Víctor Yepes

“…The optimization process considered four criteria simultaneously, using a discrete version of the SCA algorithm and a transfer function for discretization. …”
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Dynamic Gesture Recognition and Interaction of Monocular Camera Based on Deep Learning by SUNBo wen, YU Feng

“…Through convolution and fullconnected network structure, as well as optimization of parameter selection and prevention of overfitting, combined with fingertip detection and elimination algorithm, the recognition accuracy is improved. …”
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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 analytical implementation of the cost function is validated experimentally. 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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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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Enhancing electric vehicle range through real-time failure prediction and optimization: Introduction to DHBA-FPM model with an artificial intelligence approach by Yunus Emre Ekici, Teoman Karadağ, Ozan Akdağ, Ahmet Arif Aydin, Hüseyin Ozan Tekin

“…Among these, the Developed Honey Badger Algorithm with AI Approach (DHBA) emerged as the most effective, achieving a predictive accuracy improvement of 15 % over the standard Honey Badger Algorithm (HBA). …”
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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

“…Initially, four deep learning models—DenseNet161, ResNet152, and MobileNetV3 variants—are explored to determine the most suitable feature extraction method. 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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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…It is presumed that the implementation of deep learning algorithms demands a large amount of data to learn complex features automatically and this can pose a challenge for applications with lesser data to achieve generalization. …”
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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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Enhancing retail operations: Dynamic fulfilment strategies in Omnichannel retail by Hümeysa İskender, Sinem Dayanıklı, Abdullah Hulusi Kökçam, Željko Stević, Safiye Turgay, Mahmut Baydaş, Jasmina Bunevska Talevska

“…This model presents advantages such as faster delivery, cost reduction, improved stock management, increased sales, and enhanced customer satisfaction. …”
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Optimizing the Joint Replenishment and Delivery Scheduling Problem under Fuzzy Environment Using Inverse Weight Fuzzy Nonlinear Programming Method by Yu-Rong Zeng, Lin Wang, Xian-Hao Xu, Qing-Liang Fu

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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We also present the Spider Wasp Optimization (SWO) algorithm, which aims to improve performance by feature selection. …”
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Robust Optimal Sizing of a Stand-Alone Hybrid Renewable Energy System Using Machine Learning-Based Uncertainty Sets by Ali Keyvandarian, Ahmed Saif, Ronald Pelot

“…Simulation reveals a 10.7% increase in capital cost on average but a 36.2% decrease in operational cost, resulting in a 16.4% total cost reduction and an 8.1% improvement in system reliability compared to the nominal model employing point estimates. …”
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An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints by Minhui Qian, Jiachen Wang, Dejian Yang, Hongqiao Yin, Jiansheng Zhang

“…To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). …”
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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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Detection of Phosphorus in Water by Laser-Induced Breakdown Spectroscopy Based on Liquid-Solid Transformation of Graphite Substrate Combined with PLS-SVR Fusion Quantitative Analys... by Huijie Zhang, Yao Chen, Zongjie Bi, Xiaohua Che, Zhaoshuo Tian

“…To enhance sensitivity in detecting phosphorus in water via laser-induced breakdown spectroscopy (LIBS), this study integrates liquid–solid conversion on graphite substrates with a PLS-SVR fusion algorithm. Optimized laser parameters (500 mJ, 13 pulses) improved plasma excitation and signal-to-noise ratios. …”
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