Research on anode inlet pressure control strategy of PEMFC through hardware-in-the-loop test by Jing Zhang, Zhongkao Tan, Chengzhi Fan, Jingying Tan, Guoan Luo, Weiye Lu, Zhiqiang Liang, Cong Xu, Yixuan He, Xiaodong Wang, Zhongmin Wan

“…Through the HIL test, it is verified that the NLADRC algorithm is also applicable to the FCU. The model and control method proposed in this paper can be used to optimize the control of the hydrogen supply system and improve the dynamic performance of PEMFC.…”
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Integrating status-neutral and targeted HIV testing in Zimbabwe: A complementary strategy. by Hamufare D Mugauri, Owen Mugurungi, Joconiah Chirenda, Kudakwashe Takarinda, Prosper Mangwiro, Mufuta Tshimanga

“…This combined approach optimizes resource use, particularly in low- and middle-income countries, and contributes to improved health outcomes and reduced HIV transmission rates.…”
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Research on Measurement of Coal–Water Slurry Solid–Liquid Two-Phase Flow Based on a Coriolis Flow Meter and a Neural Network by Jie Liu, Lingfei Kong, Jiahao Ma, Xuemei Zhang, Chengjie Wang, Dongze Wu

“…The first correction results showed that the corrected error of the predictive model was 3.98%, a significant improvement compared to the 5.11% error measured by the X company’s meter. (2) Building on this, a second correction model was established through algorithm optimization, successfully reducing the corrected error of the predictive model to 1.01%. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…This study introduces innovative ensemble learning models that integrate the randomizable filter classifier (RFC), regression by discretization (RBD), and attribute-selected classifier (ASC) with the random forest (RF) algorithm, resulting in hybrid models (RFC-RF, RBD-RF, and ASC-RF). …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

“…The controller that is designed has many parameters, so the optimal parameter selection is very difficult. The search for optimal parameters in the swarm model controller requires optimization techniques such as the genetic algorithm (GA) to direct the search for solutions that produce the best performance. …”
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Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

“…To isolate and quantify the crack region, this research combines image thresholding, morphological operations, and contour detection with the convex hulls method and forms a novel algorithm. Two explainable AI (XAI) tools, local interpretable model-agnostic explanations (LIMEs) and gradient-weighted class activation mapping++ (Grad-CAM++) are integrated with the proposed method to enhance result clarity. …”
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A comprehensive techno-economic analysis for a PHEV-integrated microgrid system involving wind uncertainty and diverse demand side management policies by Bishwajit Dey, Laishram Khumanleima Chanu, Gulshan Sharma, Pitshou N. Bokoro

“…The research investigation employed the Differential Evolution (DE) algorithm as an optimization technique. Numerical results show that the total operating cost (TOC) of the MG system reduced from $25,575 during the base load model to $24,521 when the proposed hybrid DSM was implemented. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. We designed Wise-IoU as the model's loss function to optimize the regression accuracy of its bounding boxes and enhance robustness to low-quality samples. …”
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Resource Scheduling with Uncertain Execution Time in Cloud Computing by LI Cheng-yan, CAO Ke-han, FENG Shi-xiang, SUN Wei

“…For the problem of cloud computing resource scheduling, based on the fuzzy programming theory, a fuzzy cloud resource scheduling model under timecost constraint was set up, the uncertain execution time of tasks is represented by the triangular fuzzy number, and the target is to minimize the average value and standard deviation of the evaluation function An improved chaotic ant colony algorithm was proposed to solve the model, the elitist strategy is introduced to optimize the pheromone updating, a chaotic mapping with infinite folding times is used for chaotic search, and the adaptive chaotic disturbance mechanism is designed to enhance the global searching ability The model and algorithm were tested on the Cloudsim platform, the reliability of the model was proved, and the experimental results showed that the proposed algorithm had better performance in convergence speed, solution ability and load balance…”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. These improvements led to a 78% decrease in the number of parameters and a 68% decrease in GFLOPs. …”
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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…The distribution patterns align with established literature, confirming the algorithm's capability to effectively handle material heterogeneity and accurately capture permeability anisotropy effects on seepage field distribution.ConclusionsThe results demonstrate that the proposed algorithm achieves significantly enhanced precision in locating the seepage escape point. …”
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Short-term forecast of wind power based on the division of wind speed fluctuation characteristics by QIAO Titang, XIE Lirong, YE Jiahao, GAO Yang, DAI Bing

“…The dynamic time warping algorithm is used to mine the fluctuating wind similar data in the historical data, and a training sample data set is constructed combining with the corresponding historical wind power; a hunger game search algorithm is used to optimize the hyperparameters of the gated recurrent unit neural network, and a combined prediction model for three fluctuation stages is established. …”
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Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Ra... by Sifan Chen, Lingqi Gao, Maolu Tan, Ke Zhang, Fajin Lv

“…<b>Conclusions</b>: These findings underscore the potential of DL-CAD for lung cancer screening and the clinical value of VR in low-dose settings, but they highlight the need for improved classification algorithms.…”
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Adaptive variable channel heat dissipation control of ground control station under various work modes by Dexin Wang, Jiali Tao, Jin Lei, Xinyan Qin, Yanqi Wang, Jie Song, Tianming Feng, Yujie Zeng

“…This research introduces an Adaptive Variable Channel Control (AVCC) cooling approach using the Deep Reinforcement Learning Soft Actor-Critic (SAC) algorithm. The primary contributions of this paper include: (1) the design of a distributed cooling module featuring multiple cooling fans, which enables a variable channel cooling structure; (2) the development of a multi-module temperature control platform that simulates the heat generation conditions of each module under six work modes, providing a training environment for the cooling control algorithm; (3) the formulation of a model-free control method based on the SAC algorithm, AVCC, to optimize the cooling efficiency and endurance of the GCS. …”
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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…To alleviate such issues, this study proposes a channel estimation method by combining the sparrow search algorithm (SSA) and gated recurrent unit (GRU). In addition, this paper adds the attention mechanism to GRU to improve the robustness of the model. …”
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Remaining Useful Life Prediction Method for Bearings Based on Pruned Exact Linear Time State Segmentation and Time–Frequency Diagram by Xu Wei, Jingjing Fan, Huahua Wang, Lulu Cai

“…To improve the accuracy and robustness of bearing remaining useful life (RUL) prediction, this paper proposes a bearing RUL prediction method based on PELT state segmentation and time–frequency analysis, incorporating the Informer model for time-series modeling. …”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. …”
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Analysis of IoT-Collected Radish Growth Data Using Deep Neural Networks by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…The aim of this study was to apply genetic algorithm-based hyperparameter optimization (GA-HPO) to deep neural networks (DNNs) to classify an IoT-collected dataset on radish growth conditions, with the goal of identifying optimal growth parameters. …”
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Predicting Ship Waiting Times Using Machine Learning for Enhanced Port Operations by Min-Hwa Choi, Woongchang Yoon

“…The XGBoost Regressor (XGBR) is optimized using genetic-algorithm-based hyperparameter tuning, reducing mean squared error (RMSE) from 20.9531 to 19.6387, mean absolute error (MAE) from 13.6821 to 12.6753, and improving coefficient of determination (R2) from 0.2791 to 0.2949. …”
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Combined CNN-BiLSTM-Att tourism flow prediction based on VMD-MWPE decomposition reconstruction by Maomao Luo, Danhong Chen, Xinxing Hou, Kang Luo, Tao Wang

“…Finally, the CNN-BiLSTM prediction model, incorporating an attention mechanism and optimized using a genetic algorithm, was applied to generate the final prediction results. …”
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