An Incremental Kernel Density Estimator for Data Stream Computation by Yulin He, Jie Jiang, Dexin Dai, Klohoun Fabrice

“…Probability density function (p.d.f.) estimation plays a very important role in the field of data mining. Kernel density estimator (KDE) is the mostly used technology to estimate the unknown p.d.f. for the given dataset. …”
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Bandwidth Selection for Recursive Kernel Density Estimators Defined by Stochastic Approximation Method by Yousri Slaoui

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Wind Speed Probability Distribution Based on Adaptive Bandwidth Kernel Density Estimation Model for Wind Farm Application by Tin Trung Chau, Thu Thi Hoai Nguyen, Linh Nguyen, Ton Duc Do

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Kernel density estimation of egg attachment areas aids in revealing spatiotemporal changes in Chinese sturgeon spawning grounds by Pengsheng Li, Xuan Ban, Jinming Wu, Hui Zhang, Junyi Li, Li Shen, Zhigang Liu, Hao Du

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Adaptive Oversampling via Density Estimation for Online Imbalanced Classification by Daeun Lee, Hyunjoong Kim

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Model-enhanced spatial-temporal attention networks for traffic density prediction by Qi Guo, Qi Tan, Yue Peng, Long Xiao, Miao Liu, Benyun Shi

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Impacts of free-roaming dogs on spatiotemporal niches of native carnivores in Taiwan by Hsin-Cheng Ho, Tzung-Su Ding, Hsiao-Wei Yuan, Jo-Szu Tsai, Guo-Jing Weng, Yu-Hsiu Lin, Hsiang Ling Chen, Yu-Bo Huang, Shih-Ching Yen

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From Location Advantage to Innovation: Exploring Interprovincial Co-Funding Networks in Mainland China by Feifei Wang, Hanbai Wang, Yuxuan An, Rui Xue, Yuanke Zhang, Tianqi Hao

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Episodic Gregariousness Leads to Level‐Dependent Core Habitats: A Case Study in Eastern Copperheads (Agkistrodon contortrix) by Tyler C. Christensen, Robert Kwait, Michael Van Clef, Brooke Maslo

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Provenancing ancient materials with lead isotopes: overlap uncovered by Sarah De Ceuster, Jurian Hoogewerff, Patrick Degryse

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Strong laws of large numbers for arrays of row-wise exchangeable random elements by Robert Lee Taylor, Ronald Frank Patterson

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Kernel distribution density estimation based on cross-validation by Mindaugas Kavaliauskas

“… The kernel density estimation procedure is proposed. Parameter selection method based on cross-validation technique is analyzed. …”
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The Novel Successive Variational Mode Decomposition and Weighted Regularized Extreme Learning Machine for Fault Diagnosis of Automobile Gearbox by Yijiao Wang, Guoguang Zhou

“…The novel successive variational mode decomposition (SVMD) is presented to improve the traditional variational mode decomposition, which finds modes one after the other, and this succession helps increase convergence rate and also not extract the unwanted modes; weighted regularized extreme learning machine (WRELM) is presented to improve the traditional extreme learning machine, which uses the weight of each sample with the nonparametric kernel density estimation and can find the optimal weight for each sample. …”
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PCA mix‐based Hotelling's T2 multivariate control charts for intrusion detection system by Mo Shaohui, Gulanbaier Tuerhong, Mairidan Wushouer, Tuergen Yibulayin

“…It was compared with the conventional Hotelling's T2 control chart based on PCA and the performance of the control limits obtained with the bootstrap method was compared to the ones calculated using the most commonly used kernel density estimation. The experimental results revealed that the proposed method had better performance in intrusion detection than its counterparts.…”
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Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers by Jingling Zhang, Yusu Sun, Qinbing Feng, Yanwei Zhao, Zheng Wang

“…By optimizing the robust uncertainty model, combined with a data-driven kernel density estimation method, the distribution feature set of historical data samples can then be fitted, and finally, a distributed robust vehicle routing model for uncertain customers is established. …”
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A Copula-Based and Monte Carlo Sampling Approach for Structural Dynamics Model Updating with Interval Uncertainty by Xueqian Chen, Zhanpeng Shen, Xin’en Liu

“…Next, 95% confidence intervals of updating parameters are calculated by the nonparameter kernel density estimation (KDE) approach, which is regarded as the intervals of updating parameters. …”
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Analysis of the Spatiotemporal Heterogeneity and Influencing Factors of Regional Economic Resilience in China by Qiuyue Zhang, Yili Lin, Yu Cao, Long Luo

“…The entropy method, kernel density estimation, and spatial Durbin model are applied to examine the spatiotemporal evolution and influencing factors. …”
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An Improved Dual-Kurtogram-Based T2 Control Chart for Condition Monitoring and Compound Fault Diagnosis of Rolling Bearings by Zhiyuan Jiao, Wei Fan, Zhenying Xu

“…Then, the spectral kurtosis (SK) of Subband I and the envelope spectral kurtosis (ESK) of Subband II are formulated to construct a control limit based on kernel density estimation. Similarly, vibration data that need to be monitored are constructed into two subbands by the dual-kurtogram. …”
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Shape Prior Embedded Level Set Model for Image Segmentation by Wansuo Liu, Dengwei Wang, Wenjun Shi

“…Secondly, a shape prior term driven by kernel density estimation (KDE) is additionally introduced into the optimized LSEWR model. …”
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Revealing the decision-making practices in automated external defibrillator deployment: insights from Shanghai, China by Chaowei Wu, Yeling Wu, Lu Qiao

“…Taking Shanghai, China as the research area, we adopted the kernel density estimation and spatial autocorrelation analysis to explore the spatial distribution characteristics of AEDs. …”
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