Performance Assessment of Undifferenced GPS/Galileo Precise Time Transfer with a Refined Clock Model by Wei Xu, Pengfei Zhang, Lei Wang, Chao Yan, Jian Chen

“…Conventional Global Navigation Satellite System (GNSS) time transfer algorithms typically model receiver clock offsets as white noise for estimation, neglecting the physical characteristics of atomic clocks, which consequently limits the performance of GNSS time transfer. …”
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Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling by Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li, Yujie Huang

“…Accordingly, the proposed model synchronizes Type II peak-hour throughput with Type I off-peak experiential depth using dynamic path allocation algorithms. …”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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Analysis of Brand Communication Influence of Professional Sports Clubs Based on Complex System Discrete Model by Hui Zhang

“…Based on this, this paper studies the application of the discrete model based on the complex system in sports club to enterprise brand communication and designs a model of the impact of professional sports club on enterprise brand communication based on the SIR model and PSO algorithm. …”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Study on Finite Element Model Modification of Long-Span Suspension Bridge Based on BPANN-GA by Zi-Xiu Qin, Xi-Rui Wang, Wen-Jie Liu, Zi-Jian Fan

“…In order to improve the reliability of the finite element analysis model of long-span suspension bridges, this paper proposes a finite element model (FEM) modification method by the hybrid algorithm of backpropagation artificial neural network (BPANN) and genetic algorithm (GA) based on field measurements and vibration modal analysis. …”
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Fuzzy Multi-Agent Simulation for Collective Energy Management of Autonomous Industrial Vehicle Fleets by Juliette Grosset, Ouzna Oukacha, Alain-Jérôme Fougères, Moïse Djoko-Kouam, Jean-Marie Bonnin

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Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…Xgboost, SVM, and kriging variogram models were explored to generate ground truth datasets for the CGAN model training, and the best algorithm was employed. …”
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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study by Juan Xie, Run-wei Ma, Yu-jing Feng, Yuan Qiao, Hong-yan Zhu, Xing-ping Tao, Wen-juan Chen, Cong-yun Liu, Tan Li, Kai Liu, Li-ming Cheng

“…The application of this model can help optimize the early identification and management of high-risk patients and improve clinical decision-making. …”
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Hybrid Techniques for Short Term Load Forecasting by Saroj Panda, Papia Ray, Surender Salkuti

“…The neural model consists of weights whose optimal values are determined using various optimization approaches. …”
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Predicting postoperative nausea and vomiting using machine learning: a model development and validation study by Maxim Glebov, Teddy Lazebnik, Maksim Katsin, Boris Orkin, Haim Berkenstadt, Svetlana Bunimovich-Mendrazitsky

“…Conclusions The machine learning-based models developed in this study enabled improved PONV prediction, thereby facilitating personalized care and improved patient outcomes.…”
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A Pythagorean fuzzy MCDM model for evaluating career happiness in sports by selecting a suitable sport by JiaYan Zhu, Zeng Jiao

“…We present the MCDM algorithm for AHP and the derived AOs, offering solutions to practical numerical examples and identifying optimal sports options that improve career happiness. …”
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Hybrid modeling of adsorption process using mass transfer and machine learning techniques for concentration prediction by Jing Lv, Lei Wang

“…To improve model performance, hyperparameters were optimized using the bio-inspired Barnacles Mating Optimizer (BMO) algorithm. …”
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Multi-Condition Rolling Bearing Fault Denoising Method and Application Based on RIME-VMD by Xin Zhao, Xuebin Liu, Hanshan Li

“…The experimental results show that the RIME-VMD method can effectively remove most of the noise in the rolling bearing fault signal, and the performance evaluation indexes of this method are better than other existing optimization algorithms. …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…In response to the rapid and accurate distribution network security situation awareness requirements, this paper proposes a distribution network security situation awareness method based the distribution network topology layered model. First, a hierarchical model of the distribution network topology under the premise of optimizing the location of the synchronous phasor measuring device is constructed. …”
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Construction of Industrial Economic Management Decision Model Based on Three Parameter Interval Grey Numbers by Pao-Ching Lin, Tzu-Jung Wu, Jui-Chan Huang

“…This model characterizes the uncertainty of decision information by introducing three parameter interval grey numbers, and innovatively adopts grey relational clustering decision-making method, combined with genetic algorithm to dynamically optimize key parameters. …”
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…Based on this dataset, a novel hybrid deep learning model framework is proposed, which integrates deep learning models (EfficientNet-B7, MobileNetV3, ResNet50, and VGG16) for feature extraction with machine learning algorithms (Logistic Regression, Random Forest, AdaBoost, and Stochastic Gradient Boosting) for classification. …”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…This paper presents an advanced hybrid approach that utilizes the Quantum Chimp Optimization Algorithm (QCOA) integrated with SqueezeNet to enhance the accuracy and efficiency of DR classification significantly. …”
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A novel hybrid model based on MPA-VMD, QRMGM and KDE for carbon price prediction by Dabin Zhang, Yufeng Ye, Yongmei Fang, Jing Zhou

“…The study employed a lightweight hybrid model to forecast carbon prices. Firstly, Marine Predators Algorithm Optimized Variational Mode Decomposition (MPA-VMD) was applied to decompose the original carbon price time series to obtain optimal parameters and subsequences. …”
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