A novel method for optimizing epilepsy detection features through multi-domain feature fusion and selection by Guanqing Kong, Guanqing Kong, Shuang Ma, Shuang Ma, Wei Zhao, Wei Zhao, Haifeng Wang, Haifeng Wang, Qingxi Fu, Qingxi Fu, Jiuru Wang

“…To extract features strongly correlated with epileptic classification detection, an improved particle swarm optimization (PSO) algorithm and Pearson correlation analysis are combined. …”
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Min3GISG: A Synergistic Feature Selection Framework for Industrial Control System Security with the Integrating Genetic Algorithm and Filter Methods by Saiprasad Potharaju, Swapnali N. Tambe, G. Madhukar Rao, M. V. V. Prasad Kantipudi, Kalyan Devappa Bamane, Mininath Bendre

“…This study aims to enhance ICS security by improving attack detection through an optimized feature selection framework that balances dimensionality reduction and classification accuracy. …”
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Artificial Intelligence and MCDA in Circular Economy: Governance Strategies and Optimization for Reverse Supply Chains of Solid Waste by Joel Joaquim de Santana Filho, Arminda do Paço, Pedro Dinis Gaspar

“…The results indicate that hybrid MCDA-AI models, employing techniques, such as TOPSIS, AHP, neural networks, and genetic algorithms, enhance decision-making automation, reduce costs, and improve waste traceability. …”
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Outdoor Environment Design Optimization of an Office Building Based on Indoor Thermal Conditions and Building Energy Performance by Yaolin Lin, Tao Huang, Wei Yang, Melissa Chan, Chun-Qing Li, Mingqi Dai, Pengju Chen

“…Fourthly, the artificial neural network models were used as fitness functions for seven optimization algorithms and Pareto front solutions were obtained during the optimization process. …”
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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. …”
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Study on the fusion of improved YOLOv8 and depth camera for bunch tomato stem picking point recognition and localization by Guozhu Song, Jian Wang, Rongting Ma, Yan Shi, Yaqi Wang

“…Initially, the Fasternet bottleneck in YOLOv8 is replaced with the c2f bottleneck, and the MLCA attention mechanism is added after the backbone network to construct the FastMLCA-YOLOv8 model for fruit stalk recognition. Subsequently, the optimized K-means algorithm, utilizing K-means++ for clustering centre initialization and determining the optimal number of clusters via Silhouette coefficients, is employed to segment the fruit stalk region. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…Secondly, a C2f_RVB module is designed, which uses the RepViTBlock technique to optimize feature representation and effectively reduce the number of model parameters. …”
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A binary gridding path-planning method for plant-protecting UAVs on irregular fields by Wang-ying XU, Xiao-bing YU, Xin-yu XUE

“…In this study, we proposed a binarization multi-objective model for the irregular field area, specifically an improved non-dominated sorting genetic algorithm–II based on the knee point and plane measurement (KPPM-NSGA-ii). …”
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Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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Developing a novel approach for passive damped LCL filter and controller parameter design using PSO algorithm in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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Opportunities and challenges of quantum computing for climate modeling by Mierk Schwabe, Lorenzo Pastori, Inés de Vega, Pierre Gentine, Luigi Iapichino, Valtteri Lahtinen, Martin Leib, Jeanette Miriam Lorenz, Veronika Eyring

“…We discuss how quantum computers could accelerate climate models by solving the underlying differential equations faster, how quantum machine learning could better represent subgrid-scale phenomena in ESMs even with currently available noisy intermediate-scale quantum devices, how quantum algorithms aimed at solving optimization problems could assist in tuning the many parameters in ESMs, a currently time-consuming and challenging process, and how quantum computers could aid in the analysis of climate models. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…Traditional methods, such as Genetic Algorithms (GA) and Maximum Relevance Minimum Redundancy (MRMR), have been widely used, but bio-inspired algorithms like Ant Colony Optimization (ACO) and Ant Lion Optimizer (ALO) have shown promising results. …”
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Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels by Mohammad Hassan Adeli, Dariush Abbasi-Moghadam, Hossein Fotouhi, S. Mohammad Razavizadeh

“…Results demonstrate the superiority of our proposed design compared to the conventional scenarios with equal power allocation and fixed PS ratio algorithms with about 2 to 5 times EE improvements. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
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ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses by Yangyan Li, Tingting Chen

“…Additionally, ISCCO optimized goods allocation using a genetic algorithm enhanced integer linear programming model. …”
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An Improved Correlation Filtering Method for Tracking Maritime Small Targets of GF-4 Staring Satellite Sequence Images by Deyang Zhang, Yao Xu, Haimin Hu

“…The multi-scale features of the target based on time and space information are extracted, and the target tracking is realized by improved kernel correlation filtering algorithm. By comprehensively utilizing unscented Kalman filter model and target significance features, tracking results are optimized to improve tracking accuracy. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

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Priority Load Management for Improving Supply Reliability of Critical Loads in Healthcare Facilities Under Highly Unreliable Grids by Ndukwe Henry Ibiam, Fadi Kahwash, Jubaer Ahmed

“…It was found that the priority-based algorithm improved the reliability served to the most critical loads at the expense of the least critical. …”
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Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

“…The experimental results demonstrate that, in comparison with the currently prevalent mainstream target detection algorithms, the improved model can attain optimal recall rates R, mAP@0.5, and mAP@0.5:0.95. …”
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