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Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approach

机译：改善森林的非代表性样本预测地上生物量地图：组合机学习和空间统计方法

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Shaoqing Dai; Xiaoman Zheng; Lei Gao; Shudi Zuo; Qi Chen; Xiaohua Wei; Yin Ren;
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1. Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms [J] . Elhadi Adam, Onisimo Mutanga, Riyad Ismail, Sensors . 2014,第8期

机译：人工林内物种间生物量预测：测试高空间分辨率星载多光谱RapidEye传感器和先进的机器学习算法的实用性
2. Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach [J] . Murphy Matthew C., Poplawsky Alexander J., Vazquez Alberto L., NeuroImage . 2016,第Null期

机译：使用监督机器学习方法提高了大鼠嗅球中功能图的空间准确性
3. Spatial pattern analysis and prediction of forest fire using new machine learning approach of Multivariate Adaptive Regression Splines and Differential Flower Pollination optimization: A case study at Lao Cai province (Viet Nam) [J] . Dieu Tien Bui, Nhat-Duc Hoang, Samui Pijush Journal of Environmental Management . 2019,第MAYa1期

机译：基于多元自适应回归样条和微分花授粉优化的新型机器学习方法对森林火灾的空间格局进行分析和预测：以老街省（越南）为例
4. A Combined Analytical Modeling Machine Learning Approach for Performance Prediction of MapReduce Jobs in Cloud Environment [C] . Ehsan Ataie, Eugenio Gianniti, Danilo Ardagna, International Symposium on Symbolic and Numeric Algorithms for Scientific Computing . 2016

机译：云环境下MapReduce作业性能预测的组合分析建模机器学习方法
5. Application of Machine Learning and Statistical Learning Methods for Prediction In A Large-Scale Vegetation Map [D] . Brookey, Carla M. 2018

机译：机器学习和统计学习方法在大型植被图预测中的应用
6. Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms [O] . Timothy Dube, Onisimo Mutanga, Elhadi Adam, 2014

机译：人工林内物种间生物量预测：测试高空间分辨率星载多光谱RapidEye传感器和先进的机器学习算法的实用性
7. Supplementary material to quot;Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approachquot; [O] . Shaoqing Dai, Xiaoman Zheng, Lei Gao, 2019

机译：“改善地上生物量地下森林的非代表性样品预测”的补充材料：组合机器学习和空间统计方法“

Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approach

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