Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study by Leila Nezamabadi Farahani, Anoshirvan Kazemnejad, Mahlagha Afrasiabi, Leili Tapak

“…Then, the particle swarm optimization (PSO) and genetic algorithm (GA) were used in combination with SVR for selecting features related to pseudo-survival outcome. …”
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The Optimal Location of Interline Power Flow Controller in the Transmission Lines for Reduction Losses using the Particle Swarm Optimization Algorithm by Mehrdad Ahmadi Kamarposhti

“…This paper proposed, the optimal location of the IPFC in electrical power systems, using the particle swarm optimization algorithm. …”
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Automated Generation of Hybrid Metaheuristics Using Learning-to-Rank by Xinru Xue, Ting Shu, Jinsong Xia

“…Metaheuristic algorithms, due to their superior global exploration capabilities and applicability, have emerged as critical tools for addressing complicated optimization tasks. …”
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Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

“…To address this issue, this paper proposes a novel prediction model based on the Improved Sparrow Search Algorithm-optimized XGBoost (ISSA-XGBoost). …”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

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Application of MRI image segmentation algorithm for brain tumors based on improved YOLO by Tao Yang, Xueqi Lu, Lanlan Yang, Miyang Yang, Jinghui Chen, Hongjia Zhao

“…The remaining 223 images, along with Dataset 2, were ultimately used as the internal test set and external test set, respectively, to evaluate the model’s segmentation effect. A series of optimizations were made to the original YOLOv5 algorithm, introducing the Atrous Spatial Pyramid Pooling (ASPP), Convolutional Block Attention Module (CBAM), Coordinate Attention (CA) for structural improvement, resulting in several optimized versions, namely YOLOv5s-ASPP, YOLOv5s-CBAM, YOLOv5s-CA, YOLOv5s-ASPP-CBAM, and YOLOv5s-ASPP-CA. …”
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Design of Instrumentation and Control Components of Power Distribution Systems by Y. A. Klimenko, Y. E. Lvovich, A. P. Preobrazhensky

“…In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

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Optimization Procedures in Affine Model Checking by N. O. Garanina

“…In this paper we suggest improved algorithms for an algebraic data representation, namely, optimization algorithms for affine data structures.…”
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YOLOv8-E: An Improved YOLOv8 Algorithm for Eggplant Disease Detection by Yuxi Huang, Hong Zhao, Jie Wang

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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…This study explores the performance of hybrid bio-inspired algorithms and deep learning techniques for gene selection and cancer classification. …”
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DQN Simulation Model of Green Cooperative Market Behavior of Multi-Load Users for Optimal Evolution of New-Type Power System by ZHANG Shuo, YUAN Chunhui, LI Yingzi, XIAO Yangming, WEI Ming, HE Yunzheng

“…[Methods] First， the green cooperative market behavior and bidding behavior of multiple loads were analyzed and a multiple-load market bidding decision model was constructed. Second， the decision-making process of multiple loads and the entire transaction simulation process of the power market were constructed， and the deep reinforcement learning DQN algorithm was applied to analyze the behavior of multiple loads participating in market transactions and obtain their optimal bidding strategies. …”
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Integration of improved APF and RRT algorithms for enhanced path planning in mobile robotics by Yu Liangwu, Han Jianggui, Ma Boweng, Liu Bao, He Zhiying

“…Firstly, the mathematical model of the traditional APF algorithm was improved to solve the problems of unbalanced force and unreachable targets. …”
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Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm by Hongyan Shi, Xiaofei Wu, Guogang Wang

“…To enhance exploration capabilities and convergence speed, fractional-order characteristics and a reward feedback mechanism are introduced into the OU noise, dynamically adjusting noise intensity to improve adaptability to complex states and optimize the exploration strategy of the TD3 algorithm. …”
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Small object detection algorithm based on improved YOLOv10 for traffic sign by Yukang Zou, Scarlett Liu

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A Lightweight Detection Method for Meretrix Based on an Improved YOLOv8 Algorithm by Zhongxu Tian, Sifan Hou, Xiaoxue Yue, Xuewen Hu

“…Clam farms are typically located in remote areas with limited computational resources, making it challenging to deploy traditional deep learning-based object detection methods due to their large model size and high computational demands. To address this issue, this paper proposes a lightweight detection method, YOLOv8-RFD, based on an improved YOLOv8 algorithm, tailored for clam sorting applications. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model by Dengfeng Zhao, Haojie Li, Zhijun Fu, Bao Ma, Fang Zhou, Chaohui Liu, Wenbin He

“…A fully connected neural network layer is applied to establish a nonlinear mapping relationship between the extracted features and driving behavior categories. Bayesian optimization algorithm is adopted to automatically optimize hyperparameters of the network so as to improve training efficiency and performance of the proposed model. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…The investigation confirms that Optuna-optimized models are at least 13 % more precise than GA and PSO models. …”
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An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm by Lu Chen, Jie Tan, Tianci Wu, Zengxin Tan, Guobo Yuan, Yuhao Yang, Chiang Liu, Haoyu Zhou, Weisi Xie, Yue Xiu, Gun Li

“…The method first constructs a multi-axis robotic kinematic model to provide constraint conditions. Then, the PSO (particle swarm optimization) algorithm, which integrates penalty functions into the fitness evaluation, is used to determine the optimal welding path by simulating collective behavior within a group. …”
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