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

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A General Result on the Mean Integrated Squared Error of the Hard Thresholding Wavelet Estimator under α-Mixing Dependence by Christophe Chesneau

“…Applications are given for two types of inverse problems: the deconvolution density estimation and the density estimation in a GARCH-type model, both improve existing results in this dependent context. …”
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On strong laws of large numbers for arrays of rowwise independent random elements by Abolghassem Bozorgnia, Ronald Frank Patterson, Robert Lee Taylor

“…An application to density estimation is also given.…”
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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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Optimal Wavelet Estimation of Density Derivatives for Size-Biased Data by Jinru Wang, Zijuan Geng, Fengfeng Jin

“…A perfect achievement has been made for wavelet density estimation by Dohono et al. in 1996, when the samples without any noise are independent and identically distributed (i.i.d.). …”
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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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Evolution and Differentiation of High-Quality Development of Marine Economy: A Case Study from China by Bo Li, Chuang Tian, Zhaoyuan Shi, Zenglin Han

“…The temporal and spatial variation in the high-quality development of China’s marine economy from 2006 to 2016 is explored utilizing the nuclear density estimation, entropy, and mean standard deviation classification methods. …”
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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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The Impact of Pixel Resolution, Integration Scale, Preprocessing, and Feature Normalization on Texture Analysis for Mass Classification in Mammograms by Mohamed Abdel-Nasser, Jaime Melendez, Antonio Moreno, Domenec Puig

“…This information has been used in mammogram analysis applications such as mass detection, mass classification, and breast density estimation. In this paper, we study the effect of factors such as pixel resolution, integration scale, preprocessing, and feature normalization on the performance of those texture methods for mass classification. …”
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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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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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Predicted distribution of curl-leaf mountain mahogany (Cercocarpus ledifolius) in the Bighorn Canyon National Recreation Area. by Robert E Kissell, Michael T Tercek, David P Thoma, Kristin L Legg

“…A combination of probability density estimation and vector analysis was used to predict curl-leaf mountain mahogany distribution across the species range relative to climate space and how that relationship would affect curl-leaf mountain mahogany at a local scale. …”
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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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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…For any quantity of trap locations, the approach identified those that provide the most information, allowing optimization of trapping efficiency given either a constraint on the number of locations, or a set precision required for pest density estimation. Results suggest that BO is a powerful approach to enable optimized trap placement decisions by practitioners given finite resources and time.…”
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