Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…<b>Objectives</b>: The aim of this study is to evaluate and enhance the predictive capabilities of machine learning models for SSIs by assessing the effects of feature selection, resampling techniques, and hyperparameter optimization. …”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…In recent years, intelligent algorithms represented by data-driven algorithms and heuristic algorithms have gradually emerged, showing great potential for development in hydrodynamic noise optimization applications. …”
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Performance improvement of data offloading using Krill herd optimization algorithm by Maryam Jawad Kadhim, Rasool Sadeghi, Ahmad Shaker Abdalrada, Behdad Arandian, Reihaneh Khorsand

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DyEHS: An Integrated Dynamo–EPANET–Harmony Search Framework for the Optimal Design of Water Distribution Networks by Francesco De Paola, Giuseppe Speranza, Giuseppe Ascione, Nunzio Marrone

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Optimizing PEMFC parameter identification using improved pufferfish algorithm and CNN by Ji Li, Changiz Bastani

“…In this research, a novel approach has been proposed for enhancing the accuracy of proton exchange membrane fuel cell (PEMFC) models based on convolutional neural networks (CNNs) and an improved optimization method (called the improved pufferfish optimization algorithm). …”
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Optimal tuning of multi-PID controller using improved CMOCSO algorithm by Ying Hu, Xiongyan Liu, Hao Chen

“…To mitigate synchronization errors within a multi-PID controller system and enhance its resistance to interference, an improved competitive and cooperative swarm optimizer for constrained multi-objective optimization (CMOCSO) algorithm is employed to optimize the parameters of the multi-PID controller. …”
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Optimization Design of Hub Reducer Based on Improved Sparrow Search Algorithm by LI Jian-wei, YU Guang-bin

“…The simulation experiments with other four algorithms on 12 benchmark functions show that Issa improves the global optimal search ability and avoids the algorithm from falling into local optimization. …”
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Spatial Layout Optimization in Urban Renewal Based on Improved NSGAII Algorithm by Xuan Han, Baishu Xia

“…A multi-objective optimization method based on the improved non-dominated sorting genetic algorithm II was proposed to address the problem of spatial layout optimization in urban renewal. …”
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Comparative Analysis of Convergence and Performance of Improved Northern Goshawk Optimization Algorithm by ZHENG Xinyu, LI Yuan, LIU Xiaolin

“…In order to solve the problems of the northern goshawk optimization (NGO) algorithm, which quickly falls into local optimal, an improved northern goshawk optimization (INGO) algorithm is proposed in this paper. …”
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Pipeline corrosion rate prediction model using BP neural network based on improved sparrow search algorithm by Shuhui XIAO, Chuanjia DU, Chengjun WANG

“…Methods This paper proposes a pipeline corrosion rate prediction model using an optimized BP neural network based on an improved Sparrow Search Algorithm to address the aforementioned disadvantages. …”
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A new method of task aggregation and optimization allocation for multiple groups collaborative task networks by WeiWei Du, XiaoWei Chen

“…Abstract As task diversity and inter-task relationship complexity grow, optimal formation power allocation is key to improving task execution efficiency. …”
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A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System by Syazwan Ahmad Sabri, Siti Rafidah Abdul Rahim, Azralmukmin Azmi, Syahrul Ashikin Azmi, Muhamad Hatta Hussain, Ismail Musirin

“…The Marine Predator Algorithm (MPA) and Osprey Optimization Algorithm (OOA) are nature-inspired metaheuristic techniques used for optimizing the location and sizing of distributed generation (DG) in power distribution systems. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…Simulation results demonstrate that the proposed algorithm reduces the average path length by 15.4% and 7.5% compared to traditional genetic algorithm and particle swarm optimization, respectively, while improving computational efficiency by 45.5% and 16.8%.…”
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Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. …”
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Stability optimization of dynamic migration algorithm for Post-Copy of virtual machine based on KVM by Shuangxi CHEN, Ruoyan ZHAO, Hui LIU, Chunming WU, Wei RUAN

“…The dynamic migration technology of virtual machine provides a strong support for the resource scheduling of virtualization system.As one of the two core algorithms of virtual machine dynamic migration, Post-Copy algorithm has been a hot issue for scholars at home and abroad for its advantages of stable migration time and short migration downtime.The fault tolerance mechanism of virtual machine, the connection between the transfer mode of memory page and the page missing error during the migration process, and the source code of QEMU-KVM platform were studied.A fault tolerant method based on transaction synchronization was proposed to improve the stability of the Post-Copy migration algorithm.The experimental results show that the proposed algorithm can ensure the fast repair of deep end virtual machine failure, target virtual machine failure and network fault during the migration process, and solve the stability problem at a small cost.The method proposed effectively improves the stability of the Post-Copy migration algorithm, and provides reference for the future optimization research direction.…”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…A multi-objective optimization model for suspension bridges is presented, which uses layout and dimension parameters as design variables while aiming to reduce cumulative material costs and improve the safety factor, under the premise of meeting design requirements. …”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

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Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm by Huakun Jia, Hanbo Zeng, Jiyan Zhang, Xiangyang Wang, Yang Lu, Liandong Yu

“…By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Hub-and-spoke network design to optimize government subsidy costs for maritime transportation in Indonesia by Windra Priatna Humang, Djoko Prijo Utomo, Hasriwan Putra, Dedy Arianto, Rutma Pujiwat, Sucipto, Dwi Phalita Upahita, Nur Fitriana, Maharani Almira Salsabilla, Yustina Niken Raharina Hendra, Asep Yayat Nurhidayat, Mega Novetrishka Putri, Mohamad Ivan Aji Saputro, Amelia Santoso, Ivan Kristianto Singgih, Dina Natalia Prayogo, Indri Hapsari, Olyvia Novawanda, Stefanus Soegiharto, Jerry Agus Arlianto

“…This study introduces a hub-and-spoke model integrated with Milk Run Time Windows (MRTW) to enhance cost efficiency and optimize subsidy expenditures. …”
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