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Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river 期刊论文
, 2020, 卷号: 142
作者:  Phan T.-T.-H.;  Nguyen X.H.
收藏  |  浏览/下载：22/0  |  提交时间：2020/07/28
Autoregressive moving average model  Cost effectiveness  Disaster prevention  Forecasting  Learning algorithms  Water levels  Water resources  Auto-regressive integrated moving average  Computational time  Cost-effective solutions  Linear and nonlinear models  Physically based models  Statistical machine learning  Time series forecasting  Water level forecasting  Machine learning  data set  flood forecasting  forecasting method  hydrological modeling  machine learning  numerical model  performance assessment  river water  water level  Hanoi  Red River [Asia]  Viet Nam  
Growth, physiological responses and wood production of an Acacia auriculiformis plantation in southern Vietnam following mid-rotation thinning, application of phosphorus fertiliser and organic matter retention 期刊论文
, 2020, 卷号: 472
作者:  Huong V.D.;  Mendham D.S.;  Beadle C.;  Hai N.X.;  Close D.C.
收藏  |  浏览/下载：24/0  |  提交时间：2020/07/28
Biogeochemistry  Fertilizers  Organic compounds  Phosphorus  Physiological models  Physiology  Wood products  Acacia auriculiformis  Average diameter  Organic matter retention  Photosynthetic rate  Physiological response  Resource Constraint  Silvicultural management  Thinning regimes  Forestry  concentration (composition)  fertilizer application  growth  leaf area index  nitrogen  phosphorus  physiological response  plantation forestry  shrub  thinning  wood quality  Fertilizers  Forestry  Organic Compounds  Phosphorus  Physiology  Wood Products  Viet Nam  Acacia  Acacia auriculiformis  
Modeling and predicting dengue fever cases in key regions of the Philippines using remote sensing data 期刊论文
ASIAN PACIFIC JOURNAL OF TROPICAL MEDICINE, 2019, 卷号: 12, 期号: 2, 页码: 60-66
作者:  Pineda-cortel, Maria Ruth B.;  Clemente, Benjie M.;  Pham Thi Thanh Nga
收藏  |  浏览/下载：20/0  |  提交时间：2019/10/08
Dengue fever  Climate change  Remote sensing data  Autoregressive Integrated Moving  Average models