Showing 41 - 50 results of 50 for search '"kernel density estimation"', query time: 0.05s Refine Results
  1. 41

    Spatiotemporal evolution and driving factors of the synergistic effects of pollution control and carbon reduction in China by Qinggang Meng, Xiaolan Chen, Hui Wang, Wanfang Shen, Peixin Duan, Xinyue Liu

    Published 2025-01-01
    “…The distribution patterns, transition probabilities, and driving mechanisms of the CCD of PCCR are explored using kernel density estimation, Markov chains, and geographically and temporally weighted regression (GTWR). …”
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  2. 42

    Estimation the pH of CO2-saturated NaCl solutions using gene expression programming: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Parirokh Ebrahimi, Moein Kafi, Hamed Nikravesh, Yousef Kazemzadeh

    Published 2025-03-01
    “…A cumulative frequency plot of absolute relative error showed all data points had errors below 0.102, with over 90 % below 0.0615. Kernel density estimation plots confirmed the model generally underestimated pH values. …”
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  3. 43
  4. 44

    Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodet... by Tong Liu, Mingshi Wang, Mingya Wang, Qinqing Xiong, Luhao Jia, Wanqi Ma, Shaobo Sui, Wei Wu, Xiaoming Guo

    Published 2025-01-01
    “…Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation. Geodetector and a genetic algorithm optimized random forest model (GA-RF) were employed to quantify the dominant factors and precisely identify pollution sources. …”
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  5. 45

    Status and annual change of vulnerability among middle-aged and elderly people with cardiometabolic multimorbidity in a division of Xinjiang Production and Construction Corps, 2017... by Ziqi WANG, Jieting CHEN, Mei ZHANG, Mingxia JING

    Published 2024-11-01
    “…The entropy weighting method was used to dynamically evaluate the vulnerability level of the CMM population from 2017 to 2021. Kernel density estimation was used to analyze the spatial and temporal evolution characteristics of the vulnerability level of the CMM population in different community types. …”
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  6. 46
  7. 47

    A reliance on human habitats is key to the success of an introduced predatory reptile. by Tom Major, Lauren Jeffrey, Guillem Limia Russel, Rebecca Bracegirdle, Antonio Gandini, Rhys Morgan, Benjamin Michael Marshall, John F Mulley, Wolfgang Wüster

    Published 2025-01-01
    “…We investigated snake home range size using Autocorrelated Kernel Density Estimators (AKDE). Using AKDE-weighted Habitat Selection Functions we identified preferences for habitat features in a mosaic of habitats, and we used Integrated Step Selection Functions to further explore how these features influence movement. …”
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  8. 48

    Effects of emigration on home range and behavior of Atlantic spotted dolphins (Stenella frontalis) by Brittini A. Hill, Denise L. Herzing, Jeremy M. Bono

    Published 2024-04-01
    “…We examined the home ranges for LBB residents on LBB (2005–2012), LBB immigrants on GBB (2013–2020), and GBB residents on GBB (2013–2020). Fixed kernel density estimators revealed LBB immigrant dolphins maintained significantly larger home ranges (34–43%) and core areas (42–94%) than both LBB and GBB residents. …”
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  9. 49

    Space use of polar bears (Ursus maritimus) in Davis Strait in relation to sea ice and harp seals (Pagophilus groenlandicus) by Larissa Thelin, Evan Richardson, Garry Stenson, Erik Hedlin, Andrew E. Derocher

    Published 2025-01-01
    “…Polar bears (n = 18) tracked in 1991–2001 for 7–12 months had a mean 95% minimum convex polygon (MCP) home range size of 108 146 km2 (standard error of the mean (SE) = 18 252 km2) and a mean 95% kernel density home range size (kernel density estimate (KDE)) of 76 863 km2 (SE = 12 260 km2). …”
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  10. 50

    Cluster Candidates with Massive Quiescent Galaxies at z ∼ 2 by Tomokazu Kiyota, Makoto Ando, Masayuki Tanaka, Alexis Finoguenov, Sadman Shariar Ali, Jean Coupon, Guillaume Desprez, Stephen Gwyn, Marcin Sawicki, Rhythm Shimakawa

    Published 2025-01-01
    “…We adopt a Gaussian kernel density estimate with two different spatial scales (10″ and 60″) to draw a density map of massive ( $\mathrm{log}({M}_{* }/{M}_{\odot })\gt 10.5$ ) and quiescent ( $\mathrm{log}(\mathrm{sSFR}\,[{\mathrm{yr}}^{-1}])\lt -10$ ) galaxies at z  ∼ 2. …”
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