A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…To minimize redundant information, we propose an improved Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm for selecting the optimal feature subset, ensuring both the efficiency and accuracy of fatigue recognition. …”
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Energy-efficient optimization strategy based on elastic data migration in big data streaming platform by Yonglin PU, Xiaolong XU, Jiong YU, Ziyang LI, Binglei GUO

“…Focused on the problem that the stream computing platform was suffering from the high energy consumption and low efficiency due to the lack of consideration for energy efficiency in designing process, an energy-efficient optimization strategy based on elastic data migration in big data streaming platform (EEDM-BDSP) was proposed.Firstly, models of the load prediction and the resource judgment were set up, and the load prediction algorithm was designed, which predicted the load tendency and determine node resource occupancy, so as to find nodes of resource overload and redundancy.Secondly, models of the resource constraint and the optimal data migration were set up, and the optimal data migration algorithm was proposed, which data migration for the purpose of improving node resource utilization.Finally, model of the energy consumption was set up to calculate the energy consumption saved by the cluster after data migration.The experimental results show that the EEDM-BDSP changes node resources in the cluster can responded on time, the resource utilization and the energy-efficient are improved.…”
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Optimizing multimodal timetable synchronization of intercity railway and metro for the first service period during holidays by Yan Liu, Quan Zhang, Xuan Li, Yang Shi

“…To solve the model, an improved artificial bee colony algorithm (ABC) is designed, incorporating adaptive neighbour search and simulated annealing techniques. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…Furthermore, maintenance tasks are adaptively scheduled using built-in reinforcement learning (RL) and optimized model parameters are fine-tuned for improved predictive accuracy using Bayesian optimization. …”
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Maritime Port Freight Flow Optimization with Underground Container Logistics Systems Under Demand Uncertainty by Miaomiao Sun, Chengji Liang, Yu Wang, Salvatore Antonio Biancardo

“…The model is solved using a hybrid algorithm combining an improved Genetic Algorithm and Simulated Annealing (GA-SA) with Deep Q-Learning (DQN). …”
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A Detection Line Counting Method Based on Multi-Target Detection and Tracking for Precision Rearing and High-Quality Breeding of Young Silkworm (<i>Bombyx mori</i>) by Zhenghao Li, Hao Chang, Mingrui Shang, Zhanhua Song, Fuyang Tian, Fade Li, Guizheng Zhang, Tingju Sun, Yinfa Yan, Mochen Liu

“…This method combines an improved detector, incorporating an optimized multi-scale feature fusion module and the Efficient Multi-Scale Attention Fusion Cross Stage Partial (EMA-CSP) mechanism, with an optimized tracker (based on ByteTrack with improved detection box matching), alongside the implementation of a ‘detection line’ approach. …”
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Multi-Objective Optimization Method for High-Efficiency and Low-Consumption Wire Rope Greasing Process by Fan Zhou, Yuemin Wang, Ruqing Gong, Binghui Tang

“…Weight coefficients are introduced to transform the multi-objective optimization model into a single-objective optimization model, which is then solved using an improved genetic algorithm. …”
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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

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Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

“…The simulation results are validated against data from field tests. Second, an improved particle swarm optimization (PSO) algorithm is introduced to optimize the weights and thresholds of a backpropagation neural network (BPNN). …”
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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

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Research on optimization design and obstacle crossing performance of variable configuration swing arm track robot by TIAN Haibo, SU Xin, JI Kangmin

“…The improved NSGA-II algorithm is used to solve this model, yielding structural design parameters with the best obstacle-crossing performance. …”
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Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty by Junjie Qiao, Xiaofang Meng, Weigang Zheng, Pengxue Huang, Tiefeng Xu, Yupeng Xu

“…The constraints, including node voltage and energy storage device, are considered, and the model is solved using the improved grey wolf optimization algorithm. …”
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Optimizing chemotherapeutic targets in non-small cell lung cancer with transfer learning for precision medicine. by Varun Malik, Ruchi Mittal, Deepali Gupta, Sapna Juneja, Khalid Mohiuddin, Swati Kumari

“…It reached 98.264% and 97.344% on the KIBA and Binding-DB datasets, respectively, indicating improvements of 8.608% and 8.957% over baseline models.…”
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Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

“…Ten topographic and environmental conditioning factors were selected as model inputs. We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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Directed Fuzzy Edge Graphs Under q-ROF Environment: A Framework for Optimal Pathfinding by Nazia Nazir, Tanzeela Shaheen, Wajid Ali, Md Rafiul Hassan, Mohammad Mehedi Hassan

“…The core contribution is a novel path-finding algorithm based on Hamacher operators and an improved score function, which identifies optimal paths between nodes under uncertainty. …”
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Exploration of the Ignition Delay Time of RP-3 Fuel Using the Artificial Bee Colony Algorithm in a Machine Learning Framework by Wenbo Liu, Zhirui Liu, Hongan Ma

“…The framework—referred to as CGD-ABC-BP—integrates randomized initialization, conjugate gradient descent (CGD), the artificial bee colony (ABC) algorithm, and L2 regularization to enhance convergence stability and model robustness. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. …”
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MASIP: A Methodology for Assets Selection in Investment Portfolios by José Purata-Aldaz, Juan Frausto-Solís, Guadalupe Castilla-Valdez, Javier González-Barbosa, Juan Paulo Sánchez Hernández

“…This paper proposes a Methodology for Assets Selection in Investment Portfolios (MASIP) focused on creating investment portfolios using heuristic algorithms based on the Markowitz and Sharpe models. …”
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Enhanced Defect Detection in Additive Manufacturing via Virtual Polarization Filtering and Deep Learning Optimization by Xu Su, Xing Peng, Xingyu Zhou, Hongbing Cao, Chong Shan, Shiqing Li, Shuo Qiao, Feng Shi

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Coordinated optimization of control parameters for suppressing transient overvoltage in wind power DC transmission systems by Jie Zhao, Jinqiu Dou, Ming Li, Fangjie Wu, Xiaolin Shen, Yilin Liang, Lei Shang

“…Case studies validate the effectiveness of the proposed model and method. The results indicate that the improved genetic algorithm, SEGA, proposed in this paper, effectively suppresses overvoltage at the grid connection point of wind turbines. …”
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