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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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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Unraveling the spatial distribution and influencing factors of 'Bengke' traditional houses in Luhuo County, Western Sichuan. by Siwei Yu, Ding Fan, Ma Ge, Zihang Chen

“…The study utilizes spatial statistical methods, including Average Nearest Neighbor Analysis, Getis-Ord Gi*, and Kernel Density Estimation, to identify significant clustering patterns of Bengke architecture. …”
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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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Optimal configuration of dynamic VAR compensators considering uncertainty and correlation by Xiaoming Mao, Zijing Qiu, Shengbo Chen

“…First, a series of power‐flow scenarios are generated with uncertainty and correlation considered, where nonparametric kernel density estimation is used to predict the marginal distribution of wind speeds and combined Copula function is employed to characterize correlations between nearby wind farms. …”
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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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New-type urbanization and rural revitalization: A study on the coupled development of the Yangtze River Economic Belt, China. by Yan Wang, Ling Wang

“…Subsequently, it carries out a comprehensive analysis concerning their coupled relationship with the relative development degree model (RDDM), coupled coordination degree model (CCDM), Dagum Gini coefficient, kernel density estimation, and Tobit model. The findings drawn from the study indicate from 2011 to 2022, NTU and RR in the Yangtze River Economic Belt (YREB) have exhibited a consistent upward trajectory, but lagging NTU disorders are widely distributed and numerous. …”
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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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Analysis on the spatiotemporal pattern and driving force of the spatial deviation index of grain and economy in counties in China. by Jia Chen, Kuan Zhang

“…Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China's county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. …”
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A linear tessellation model for the identification of "food desert": A case study of Shanghai, China. by Lu Wang, Yakun He, Zhonghai Yu, Hongrui Wang, Wenjuan Ye, Xin Li, Yingping Liu, Junxiao Zhang

“…Firstly, the network kernel density estimation using a linear tessellation model is used to measure the travel-mode-based food accessibility. …”
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Measurement and spatiotemporal evolution characteristics of dietary diversity among Chinese residents by Guangyuan Qin, Miaomiao Li, Shiwen Quan

“…On this basis, the paper employs analysis methods such as kernel density estimation, spatial correlation test, and Dagum’s Gini coefficient to analyze the regional characteristics, differences, and trends of change in dietary diversity.ResultsDuring the study period, the dietary diversity among Chinese residents showed an increasing trend. …”
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Recognition of Functional Areas Based on Call Detail Records and Point of Interest Data by Guang Yuan, Yanyan Chen, Lishan Sun, Jianhui Lai, Tongfei Li, Zhuo Liu

“…The impact of diverse geographical area subdivisions on the accuracy of UFA recognition is discussed, and a k-means clustering method for dynamic call detail record data and kernel density estimation technique for static point of interest data are established at the traffic analysis zone level. …”
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Exploring synergistic evolution of carbon emissions and air pollutants and spatiotemporal heterogeneity of influencing factors in Chinese cities by Xue Zhao, Bilin Shao, Jia Su, Ning Tian

“…The spatiotemporal co-evolution of urban carbon emissions and air pollutants was analyzed through map visualization and kernel density estimation, revealing non-equilibrium and heterogeneity. …”
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Dynamic Spatiotemporal Causality Analysis for Network Traffic Flow Based on Transfer Entropy and Sliding Window Approach by Senyan Yang, Lianju Ning, Xilong Cai, Mingyu Liu

“…A combination of Gaussian kernel density estimation and sliding window approach is proposed to calculate the transfer entropy and construct dynamic spatiotemporal causality graphs based on the causality significance test. …”
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