Multi-Timescale Nested Hydropower Station Optimization Scheduling Based on the Migrating Particle Whale Optimization Algorithm by Mi Zhang, Guosheng Zhou, Bei Liu, Dajun Huang, Hao Yu, Li Mo

“…Validation on classical test functions and the Jiangpinghe River of the multi-timescale nested optimal scheduling model demonstrates that MPWOA exhibits faster convergence and stronger optimization capabilities and significantly improves power generation. …”
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Optimization of Multi-Energy Grid Integration and Energy Storage in Low-Carbon Power Systems Based on the TCM-MBZOA Algorithm: A Case Study of Yunnan Province by Yang Li, Guoen Zhou, Jiaqi Xue, Junwei Yang, Shi Yin

“…To address this limitation, this paper proposes a multi-source coordinated optimization strategy based on a bi-level programming model and an improved tent chaotic mapping-memory backtracking zebra optimization algorithm (TCM-MBZOA). …”
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Optimization Study of Centrifugal Fan Volute Parameters based on Non-dominated Sorting Genetic Algorithm III Algorithm by J. L. Li, X. J. Wang, H. Gong, J. J. Wang

“…The BP neural network provided highly accurate fitting and predictions, yielding a reliable surrogate model. After optimization, the centrifugal fan’s Q increased by 2.29%, and η improved by 2.96%. …”
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Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…Additionally, we developed a Multi-Objective Genetic Algorithm (MOGA)-enhanced RNN model to optimize hyperparameters and achieve accurate traffic speed predictions. …”
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Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model by JIANG Tao, XU Cong, JIA Shaohui, WANG Shen, ZHANG Yajian

“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

“…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
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High Quality Power Supply Service Mode Considering Service Life of Mitigation Equipment Against Voltage Sag by Pei LI, Yongjun YU, Zhiquan MA, Chongkai CAI

“…The improved genetic algorithm is used to solve the model. …”
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A Study on Hysteresis Stiffness Model and Parameter Identification of Harmonic Gear Transmission based on Genetic Characteristic by Linfeng Qiu, Manyi Chen, Gang Song, Jie Zhang, Ran Yang, Han Zhang

“…Based on the experimental data，particle swarm optimization algorithm is used to identify the model parameters. …”
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Robust Bi-Objective Optimization and Dynamic Modeling of Hydropneumatic Suspension Unit Considering Real Gas Effects by Di Sun, Moonsuk Chang, Jinho Kim

“…The optimized design based on a metamodel and a hybrid metaheuristic algorithm resulted in an 81.4% reduction in peak lateral forces and a 53.3% improvement in acceleration robustness, which marks a significant increase in suspension system durability. …”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…The Adam optimizer is introduced to accelerate model training and improve model convergence. …”
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Integrating feedback control for improved human-structure interaction analysis by Santiago A. Lopez, Daniel Gomez, Albert R. Ortiz, Sandra Villamizar

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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…Finally, optimized the path aggregation network of the model to enhance the feature fusion ability of the network.ResultsThe experimental results showed that the improved Our⁃YOLOv5s model had a mAP of 98.4% and a detection speed of 64 s-1 in the dataset, which was 2.4% and 6 s-1 higher than the original model, respectively.ConclusionThe model can meet the real⁃time detection requirements of marine fish.…”
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Generative Target Tracking Method with Improved Generative Adversarial Network by Yongping Yang, Hongshun Chen

“…In this paper, we proposed a target tracking algorithm based on the conditional adversarial generative twin networks, using the improved you only look once multitarget association algorithm to classify and detect the position of the target to be detected in the current frame, constructing a feature extraction model using generative adversarial networks (GANs) to learn the main features and subtle features of the target, and then using GANs to generate the motion trajectories of multiple targets, finally fuzing the motion and appearance information of the target to obtain the optimal match. …”
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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
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Cloud federation three-layer architecture: game-theoretic QoS modeling by MA Kun, HU Chuangyue, ZHANG Yuzhi, MA Fangchao, WANG Xiaodong, DANG Zhonghua, XIAO Wenhong, CHEN Shuangxi

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Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model by Mahir Mohammed Sharif Adam, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Samah Al Zanin

“…Finally, the parameter tuning of the fusion models is performed by using the Hiking Optimisation Algorithm (HOA) method. …”
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Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

“…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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Structural Parameter Optimization of the Vector Bracket in a Vertical Takeoff and Landing Unmanned Aerial Vehicle by Wenshuai Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qingzheng Liu, Qiang Liu, Yuxiang Tian

“…The functionality of unmanned aerial vehicles (UAVs) in agricultural applications was improved by optimizing the parameters of the vector bracket in a vertical takeoff and landing UAV to maximize thrust and lift-to-drag ratio. …”
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Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization by Chen Fei, Zhuo Lu, Weiwei Jiang, Liang Zhao, Fan Zhang

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A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
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