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在“自然资源管理”中，命中：73条，耗时：小于0.01 秒

1.Pollination and seed set of an obligatory outcrossing plant in an urban-peri-urban gradient

作者：Hans A.F. Verbovena ; Wim Aertsena ; Rein Brysb ; c ; Martin Hermya ; Martin.Hermy@ees.kuleuven.be" class="auth_mail

关键词：Trifolium repens ; White clover ; Bees ; Reproductive success ; Fragmentation ; Urban ecology

刊名：Perspectives in Plant Ecology, Evolution and Systematics

年：41810

2.GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran

作者：Seyed Amir Naghibi ; Hamid Reza Pourghasemi…

关键词：Spring potential mapping ; Boosted regression tree ; Classification and regression tree ; Random forest ; GIS ; Iran

刊名：Environmental Monitoring and Assessment

出版者：Springer Netherlands

年：2016

3.Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression

作者：Manish Kumar Goyal (1)

关键词：Streamflow ; M5 model tree ; Discrete wavelet transform ; Regression ; Forecast

刊名：Water Resources Management

年：2014

4.A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping

作者：Seyed Amir Naghibi ; Hamid Reza Pourghasemi

关键词：Groundwater potential mapping ; Boosted regression tree ; Classification and regression tree ; Random forest ; General linear model ; Evidential belief function ; GIS

刊名：Water Resources Management

出版者：Springer Netherlands

年：2015

5.Prediction of Water Level using Monthly Lagged Data in Lake Urmia, Iran

作者：Babak Vaheddoost ; Hafzullah Aksoy ; Hirad Abghari

关键词：Artificial neural network ; Decision tree ; Lake Urmia ; Lake water level ; Multiple regression

刊名：Water Resources Management

出版者：Springer Netherlands

年：2016

6.Probabilistic Prediction for Monthly Streamflow through Coupling Stepwise Cluster Analysis and Quantile Regression Methods

作者：Y. R. Fan ; G. H. Huang ; Y. P. Li ; X. Q. Wang ; Z. Li

关键词：Monthly streamflow prediction ; Data ; driven ; Stepwise cluster analysis ; Uncertainty ; Water resources

刊名：Water Resources Management

出版者：Springer Netherlands

年：2016

7.Estimation of forest stand volume, tree density and biodiversity using Landsat ETM Data, comparison of linear and regression tree analyses

作者：Jahangir Mohammadia ; Shaban Shataeeb ; Manoocher Babanezhadc

关键词：Forest attributes estimation ; ETM ; ; Linear ; Tree regression ; Comparison ; Hyrcanian forests

刊名：Procedia Environmental Sciences

年：2011

8.Influence of prior distributions and random effects on count regression models: implications for estimating standing dead tree abundance

作者：Matthew B. Russell (1) 1. Department of Forest Resources ; University of Minnesota ; St. Paul ; MN聽 ; 55108 ; USA

关键词：Biomass ; Carbon ; Coarse woody debris ; Forest inventory ; Markov chain Monte Carlo (MCMC) ; Zero ; inflation

刊名：Environmental and Ecological Statistics

出版者：Springer Netherlands

年：2015

9.The good, the bad, and the interested: how historical demographics explain present-day tree canopy, vacant lot and tree request spatial variability in New Haven, CT

作者：Dexter H. Locke ; Gillian Baine

关键词：Vacant lots ; Environmental stewardship ; URI ; Urban resources initiative ; New Haven

刊名：Urban Ecosystems

出版者：Springer Netherlands

年：2015

10.Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

作者：Emmanuel John M. Carranza ; Alice G. Laborte

关键词：Regression trees ; Missing data ; Hydrothermal Au–Cu deposits ; Catanduanes (Philippines) ; GIS

刊名：Natural Resources Research

出版者：Springer Netherlands

年：2016

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