Customer Clustering and Marketing Optimization in Hospitality: A Hybrid Data Mining and Decision-Making Approach from an Emerging Economy by Maryam Deldadehasl, Houra Hajian Karahroodi, Pouya Haddadian Nekah

“…Using a hybrid approach that integrates data mining with multi-criteria decision-making techniques, this study aims to identify valuable customer segments and optimize marketing strategies. This research applies the K-means clustering algorithm to classify customers from a hotel in Iran based on RMD attributes. …”
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Improved YOLO-Goose-Based Method for Individual Identification of Lion-Head Geese and Egg Matching: Methods and Experimental Study by Hengyuan Zhang, Zhenlong Wu, Tiemin Zhang, Canhuan Lu, Zhaohui Zhang, Jianzhou Ye, Jikang Yang, Degui Yang, Cheng Fang

“…The method constructs a lightweight model with a small-object detection layer, integrates the GhostNet backbone to reduce parameter count by 67.2%, and employs the GIoU loss function to optimize neck ring localization accuracy. …”
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CFD-APSO Co-Optimization for Enhanced Heat Dissipation in a <i>Camellia oleifera</i> Harvester Engine Compartment by Wenfu Tong, Kai Liao, Lefeng Zhou, Haifei Chen, Hong Luo, Jichao Liang

“…Based on these findings, the component arrangement was reconfigured to improve thermal performance. Subsequently, an “engine compartment cover parameters–temperature” correlation model was established, and the dimensional parameters of the engine compartment cover were optimized using the APSO algorithm. …”
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Co-Optimization of Speed Planning and Energy Management for Plug-In Hybrid Electric Trucks Passing Through Traffic Light Intersections by Xin Liu, Guojing Shi, Changbo Yang, Enyong Xu, Yanmei Meng

“…In the lower layer, an energy management model is constructed using the twin delayed deep deterministic policy gradient (TD3) algorithm to achieve optimal allocation of demanded power through the interaction of the TD3 agent with the truck environment. …”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…Additionally, the sparrow search algorithm (SSA) is employed to optimize hyperparameters, further improving the model’s performance. …”
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Robust Optimal Operation Method for Active Distribution Networks with Multiple Types of Regulation Resources Considering Source and Load Uncertainties by R. Ding, L. Cheng, X. Wang, Y. Yao, H. Xu, E. Zhao

“…Thirdly, the proposed model is linearized and reformulated as a convex optimization problem utilizing second-order cone relaxation techniques, and a relaxed cooperative co-evolution algorithm is im¬plemented to solve it efficiently. …”
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Fault Diagnosis Method for Vacuum Contactor Based on Time-Frequency Graph Optimization Technique and ShuffleNetV2 by Haiying Li, Qinyang Wang, Jiancheng Song

“…Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor <i>λ</i>. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. …”
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DSCW-YOLO: Vehicle Detection from Low-Altitude UAV Perspective via Coordinate Awareness and Collaborative Module Optimization by Qingqi Zhang, Hao Wang, Xinbo Wang, Jiapeng Shang, Xiaoli Wang, Jie Li, Yan Wang

“…The improved model also achieves the highest F1-score, indicating an optimal balance between precision and recall.…”
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Control of steering wheel idle jitter based on optimization of engine suspension system with verifications using multi-sensor measurement by Shuilong He, Binqiang Chen, Zhansi Jiang, Yanxue Wang, Fuyun Liu

“…A multi-sensor-based measurement strategy was utilized to evaluate the idle jitter severity of the steering wheel. In order to improve the indicators of the decoupling degree, the vibration transmissibility, and the resonant frequency distributions of the engine suspension system, an optimization model of engine suspension system was established. …”
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Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms by Rafael Pires de Lima, Yue Chen, Youzuo Lin

“…Furthermore, based on several kinds of linear and artificial neural networks algorithms, a list of models was constructed, trained, validated, and tested with 42‐month MeV electron observations from Van Allen Probes. …”
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Optimizing Automatic Voltage Control Collaborative Responses in Chain-Structured Cascade Hydroelectric Power Plants Using Sensitivity Analysis by Li Zhang, Jie Yang, Jun Wang, Lening Wang, Haiming Niu, Xiaobing Liu, Simon X. Yang, Kun Yang

“…Subsequently, a regional-voltage-coordinated regulation model is developed using sensitivity analysis, followed by the establishment of a mathematical model, solution algorithm, and operational procedure for multi-station AVC-coordinated response optimization. …”
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Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…The obtained segmentation results suggest promising directions for future research, especially in the early detection of thyroid nodules. Deploying this algorithm on mobile devices offers a practical solution for early diagnosis and is likely to improve patient outcomes.…”
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Ground-Truth-Free 3D Seismic Denoising Based on Diffusion Models: Achieving Effective Constraints Through Embedded Self-Supervised Noise Modeling by Zhonghan Zhang, Guihe Qin, Yanhua Liang, Minghui Sun, Yingqing Wang, Jiaru Song

“…Furthermore, the algorithm integrates the noise distribution estimation network into the diffusion model to further guide and refine the sampling process, thereby optimizing computational complexity and improving detail representation. …”
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Study on the Lightweighting Strategy of Target Detection Model with Deep Learning by Junli Hu

“…Aiming at the high miss detection and false detection rate of traditional SSD (single shot multibox detector) target detection algorithm in target detection, this paper proposes a lightweight detection algorithm for deep learning target detection model in order to improve the detection accuracy. …”
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A Snow Depth Downscaling Algorithm Based on Deep Learning Fusion of Enhanced Passive Microwave and Cloud-Free Optical Remote Sensing Data in China by Zisheng Zhao, Xiaohua Hao, Donghang Shao, Wenzheng Ji, Tianwen Feng, Qin Zhao, Wenxin He, Liyun Dai, Zhaojun Zheng, Yan Liu

“…When compared with downscaling algorithms utilizing the raw TB data and the traditional random forest model, the CETB data and FT-Transformer model optimize the RMSE by 10.08% and 4.84%, respectively, which demonstrates the superiority of FTSD regarding data sources and regression methods. …”
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An RMSprop-Incorporated Latent Factorization of Tensor Model for Random Missing Data Imputation in Structural Health Monitoring by Jingjing Yang

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RESEARCH ON KEYWORD MINING OF ACADEMIC LIBRARY SUBJECT SERVICE by Fan Zhang

“…Empirical research has shown that the subject service model based on keyword mining can effectively improve the level of subject service in libraries, providing users with more accurate and comprehensive information resource services. …”
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Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA by Zheng Ma, Rui Zhang, Lang Gao

“…A 5G core network DDoS attack detection model is been proposed which utilizes a binary improved non-Bald Eagle optimization algorithm (Sin-Cos-bIAVOA) originally designed for IoT DDoS detection to select effective features for DDoS attacks. …”
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Integrating Advanced Techniques: RFE-SVM Feature Engineering and Nelder-Mead Optimized XGBoost for Accurate Lung Cancer Prediction by Sarah Ayad, Hamdi A. Al-Jamimi, Ammar El Kheir

“…Our methodology combines Recursive Feature Elimination with Support Vector Machines (RFE-SVM) for effective feature selection and employs the XGBoost ensemble learning algorithm for classification, optimized using the Nelder-Mead algorithm. …”
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A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

“…Its master stage uses one out of three different algorithms—Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), or the Multi-Objective Ant Lion Optimizer (MOALO)—while the slave stage is always performed by a load flow analyzer. …”
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