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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Comparative Analysis of YOLOv8 and HSV Methods for Traffic Density Measurement by Prof. I Gede Pasek Suta Wijaya, Muhamad Nizam Azmi, Ario Yudo Husodo

“…The primary objective is to highlight the strengths and limitations of each method in terms of accuracy and reliability in traffic density estimation. The choice of segmenting the asphalt area rather than vehicle objects is justified by the need to understand how different segmentation approaches affect traffic density measurements. …”
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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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Improving Thermospheric Density Predictions in Low‐Earth Orbit With Machine Learning by Giacomo Acciarini, Edward Brown, Tom Berger, Madhulika Guhathakurta, James Parr, Christopher Bridges, Atılım Güneş Baydin

“…We show that by using the same inputs, the ML models we designed are capable of consistently improving the predictions with respect to state‐of‐the‐art empirical models by reducing the mean absolute percentage error (MAPE) in the thermospheric density estimation from the range of 40%–60% to approximately 20%. …”
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Research on optimal arrangement strategy of top coal caving support sensors based on vibration characteristics of coal and gangue by WANG Yao, YANG Shanguo, WU Mingke, MENG Bin, YANG Zheng, LIU Houguang

“…Finally, the probability density functions of target features were estimated by the kernel density estimation method. The K-L（Kullback-Leibler） divergence was used to evaluate the approximation between combined signal of each measuring point and the complete signal and the difference between characteristics of coal and gangue. …”
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Quality-related and Quality-irrelevant Fault Detection and Diagnosis in Batch Fermentation Process Based on NSSAE by Zhong LIU, Zheng ZHANG, Xuyang LOU, Jinlin ZHU

“…Upon which, kernel density estimation was used to calculate the thresholds for the indicators. …”
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Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations-A case study of the Xi'an metropolitan area. by Ke Liu, Xu Bo, Wang Zhaoping, Ran Du, Chen Heng

“…This article compares the population agglomeration characteristics of the Xi'an metropolitan area in western China with those of metropolitan areas in other regions officially approved by the Chinese government. The kernel density estimation method and Markov chain model were used to conduct the study. …”
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Decade-Long Changes in Disparity and Distribution of Transit Opportunity in Shenzhen China: A Transportation Equity Perspective by Qingfeng Zhou, Donghui Dai, Yaowu Wang, Jianshuang Fan

“…Third, we used the Dagum Gini coefficient decomposition and kernel density estimation method to explore the fair distribution of transit opportunity among groups and districts from 2011 to 2020. …”
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Spatio-temporal characteristics and analysis of influencing factors of inclusive green growth in China’s oil and gas resource industry by Xiangyu Sun, Yanqiu Wang

“…The study delineates its spatial and temporal evolution, spatial correlation, and influential variables using kernel density estimation, exploratory spatial data analysis (ESDA), and geographically and temporally weighted regression (GTWR). …”
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Facilitating or Hindering? The Impact of Low-Carbon Pilot Policies on Socio-Ecological Resilience in Resource-Based Cities by Yanran Peng, Zhong Wang, Yunhui Zhang, Wei Wang

“…Focusing on a panel of 114 resource-based cities in China, spanning from 2003 to 2022, this study employs a range of methodologies, including kernel density estimation, the Difference-in-Differences Model, Spatial Difference-in-Differences, Mediation Analysis, K-means Clustering, and Dual Machine Learning to assess the consequences of low-carbon pilot policies on socio-ecological resilience. …”
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STAR‐ESDM: A Generalizable Approach to Generating High‐Resolution Climate Projections Through Signal Decomposition by Katharine Hayhoe, Ian Scott‐Fleming, Anne Stoner, Donald J. Wuebbles

“…It uses signal processing combined with Fourier filtering and kernel density estimation techniques to decompose and smooth any quasi‐Gaussian time series, gridded or point‐based, into multi‐decadal long‐term means and/or trends; static and dynamic annual cycles; and probability distributions of daily variability. …”
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A hydropower plant scheduling model considering the stochastic correlation between runoff and electricity prices by WU Ying, WANG Juefei, LI Junjie, WANG Kun, SHEN Yan, WU Yingjun

“…Second， the least-squares cross validation （LSCV） is applied to determine the optimal bandwidth parameter in kernel density estimation （KDE）， ensuring a good fit for discrete runoff and electricity price data. …”
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Spatial-Temporal Evolution Characteristics and Countermeasures of Urban Innovation Space Distribution: An Empirical Study Based on Data of Nanjing High-Tech Enterprises by Shuang Tang, Jingxiang Zhang, Fangqu Niu

“…Taking Nanjing as an empirical area, the spatial-temporal evolution of urban innovation space distribution was studied through methods such as average nearest neighbor, standard deviational ellipse, kernel density estimation, and exploratory spatial data analysis based on the data of high-tech enterprises identified from 2008 to 2019. …”
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Interval Prediction of Photovoltaic Power Using Improved NARX Network and Density Peak Clustering Based on Kernel Mahalanobis Distance by Wen-He Chen, Long-Sheng Cheng, Zhi-Peng Chang, Han-Ting Zhou, Qi-Feng Yao, Zhai-Ming Peng, Li-Qun Fu, Zong-Xiang Chen

“…Finally, the joint probability density is established by multivariate kernel density estimation (MKDE) to accomplish the PV power interval prediction. …”
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Diagnosis of induction motor stator faults around rotor slot harmonics using the Matrix Pencil method by Mohamed Kouadria, Zakaria Chedjara, Chun-Lien Su, Mohamed Benbouzid, Josep M. Guerrero, Babul Salam KSM Kader Ibrahim, Hafiz Ahmed

“…This method aims to avoid the limitations of the classical method based on power spectral density estimation using the periodogram. Indeed, the proposed approach offers very high frequency resolution even for very short acquisition times, thus allowing improved detection even for low amplitudes. …”
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Exploring the role of electrode density in capturing spatiotemporal dynamics of resting-state networks with EEG by Matheus Mangini Bertuzzo, Rodrigo P Rocha, Ricardo Spyrídes Boabaid Pimentel Gonçalves, Adair Roberto Soares Dos Santos, Odival Cezar Gasparotto

“…We analyze how different electrode configurations affect the precision of cortical current density estimation in EEG recordings. Using exact low-resolution electromagnetic tomography, we estimated the cortical current density in regions of interest linked to resting state networks. …”
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喀斯特生境中野猪活动模式和时间分配 by 黄杨 林建忠 汪国海 周岐海

“…2017年1月—2017年12月在弄岗国家级自然保护区布设119台红外相机，通过对红外相机拍摄的野猪（Sus scrofa）的行为活动进行分析，并采用核密度估计（kernel density estimation）、重叠指数（coefficient of overlap）和相对活动强度指数（relative activity intensity index）研究野猪的活动模式和时间分配，以探讨其对喀斯特生境的适应策略。…”
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Research on the Rapid Detection of Formaldehyde Emission From Wood-Based Panels Based on the AMSHKELM by Yinuo Wang, Huanqi Zheng, Hua Wang, Yucheng Zhou

“…Moreover, an adaptive bandwidth kernel density estimation combined with the AMSHKELM is developed to construct an interval prediction model. …”
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