Zobrazeno 1 - 9 of 9 pro vyhledávání: '"Beier Zhang"'
1
Regulation of Methane Emissions in a Constructed Wetland by Water Table Changes
Autor: Chenyan Sha, Qiang Wang, Jian Wu, Wenan Hu, Cheng Shen, Beier Zhang, Min Wang
Publikováno v: Sustainability; Volume 15; Issue 2; Pages: 1536
Riparian wetlands release greenhouse gases and sequestration carbon as well, so their carbon source and carbon sink functions have become some of the key research issues of global climate change. In this present paper, the main controllable factors o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4de77912b5f9bec5594b53086fc359c
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2
Akademický článek
Application of Machine Learning for Tracing the Origin of Metastatic Lung Cancer Tissues.
Autor: Tingting Wang, Qi Fan, Hongzhi Cai, Beier Zhang
Publikováno v: IAENG International Journal of Computer Science; Jun2023, Vol. 50 Issue 2, p359-367, 9p
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4
Effects of Online Bodyweight High-Intensity Interval Training Intervention and Health Education on the Mental Health and Cognition of Sedentary Young Females
Autor: Yingyao Fu, Liaoyan Gan, Limei Ke, Qian Di, Yao Zhang, Beier Zhang, Xindong Ma
Publikováno v: International Journal of Environmental Research and Public Health
Volume 18
Issue 1
International Journal of Environmental Research and Public Health, Vol 18, Iss 302, p 302 (2021)
This study aimed to assess the effectiveness of an online high-intensity interval training (HIIT) intervention and health education on the behaviors, mental health, and cognitive function of sedentary young females. A single-blinded, six-week, random
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::708ff1321b8fbf6e610d5021a30fbe1d
https://doi.org/10.3390/ijerph18010302
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5
Evaluation of soil quality in major grain-producing region of the North China Plain: Integrating minimum data set and established critical limits
Autor: Haidong Zhang, Beier Zhang, Jingsong Yang, Kang Tian, Biao Huang, Yongcun Zhao, Jeremy Landon Darilek
Publikováno v: Ecological Indicators. 117:106613
Understanding of the nexus between soil quality (SQ) and productivity, the heterogeneity of SQ and the restricting indicators that affect crop productivity is essential for a specific region to encourage improving of SQ while contributing to profitab
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d0365760b175ef9e6de340deff15bdeb
https://doi.org/10.1016/j.ecolind.2020.106613
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6
A comparison of machine learning algorithms for regional wheat yield prediction using NDVI time series of SPOT-VGT
Autor: Jos Van Orshoven, Stien Heremans, Michiel Stas, Beier Zhang, Qinghan Dong
Publikováno v: 2016 Fifth International Conference on Agro-Geoinformatics (Agro-Geoinformatics).
This study compares two machine learning algorithms to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) der
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::94a2e154e3b2e105e1b85105687b238e
https://doi.org/10.1109/agro-geoinformatics.2016.7577625
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7
Effect of sampling density on regional soil organic carbon estimation for cultivated soils
Autor: Yongcun Zhao, Jinsong Yang, Jeremy Landon Darilek, Zhigang Wang, Beier Zhang, Weixia Sun, Xuezheng Shi, Biao Huang
Publikováno v: Journal of Plant Nutrition and Soil Science. 175:671-680
An extensive knowledge of how sampling density affects soil organic C (SOC) estimation at regional scale is imperative to reduce uncertainty to a meaningful confidence level and aid in the development of sampling schemes that are both rational and ec
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::38ef8a37ca461c43d5612622a5ac903e
https://doi.org/10.1002/jpln.201100181
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8
Potential of ensemble tree methods for early-season prediction of winter wheat yield from short time series of remotely sensed normalized difference vegetation index andin situmeteorological data
Autor: Jos Van Orshoven, Qinghan Dong, Lieven Bydekerke, Stien Heremans, Beier Zhang
Publikováno v: Journal of Applied Remote Sensing. 9:097095
We aimed at analyzing the potential of two ensemble tree machine learning methods—boosted regression trees and random forests—for (early) prediction of winter wheat yield from short time series of remotely sensed vegetation indices at low spatial
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c40b30e015dd3de459e63684dfd35758
https://doi.org/10.1117/1.jrs.9.097095
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