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Bayesian Estimates of Changes in Russian River Runoff in the 21st Century Based on the CMIP6 Ensemble Model Simulations
AbstractBased on simulations with an ensemble of CMIP6 (Coupled Models Intercomparison Project, phase 6) climate models using Bayesian averaging, an...
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Assessment and prediction of regional climate based on a multimodel ensemble machine learning method
Accurate modeling of climate change at local scales is critical for climate applications. This study proposes a regional downscaling model...
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Flood map** based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning
Among the various natural disasters that take place around the world, flood is considered to be the most extensive. There have been several floods in...
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Ensemble forecast of tropical cyclone tracks based on deep neural networks
A nonlinear artificial intelligence ensemble forecast model has been developed in this paper for predicting tropical cyclone (TC) tracks based on the...
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Flash-flood susceptibility map**: a novel credal decision tree-based ensemble approaches
Escalation in flash floods and the enhanced devastations, especially in the arid and semiarid regions of the world has required precise map** of...
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Map** wildfire ignition probability and predictor sensitivity with ensemble-based machine learning
Wildfire ignition models can help in identifying risk factors and map** high-risk areas, which addresses an urgent issue as wildfires become...
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An Ensemble-Learning-Based Method for Short-Term Water Demand Forecasting
Short-term water demand forecasting has always been a hot research topic in the field of water distribution systems, and many researchers have...
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A Novel Approach for Predicting Water Demand with Complex Patterns Based on Ensemble Learning
Predicting urban water demand is important in rationalizing water allocation and building smart cities. Influenced by multifarious factors, water...
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Estimation of solar radiation in data-scarce subtropical region using ensemble learning models based on a novel CART-based feature selection
Solar radiation estimation is essential with increasing energy demands for industrial and agricultural purposes to create a cleaner environment,...
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Projecting future reference evapotranspiration in Iran based on CMIP6 multi-model ensemble
Reference evapotranspiration (ETo) is a key factor in the hydrologic cycle and quantifying ETo for future periods is essential for the efficient...
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Prediction of embankments dam break peak outflow: a comparison between empirical equations and ensemble-based machine learning algorithms
To accurately predict dam break peak outflow ( Q p ), two standalone [random tree (RT), instance-based k- nearest neighbors learning (IBK)] and four new...
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Future changes in marine heatwaves based on high-resolution ensemble projections for the northwestern Pacific Ocean
Marine heatwaves (MHWs) are oceanic conditions characterized by extremely high sea surface temperature (SST) anomalies that last for several days to...
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Calibration and uncertainty analysis of integrated SWAT-MODFLOW model based on iterative ensemble smoother method for watershed scale river-aquifer interactions assessment
River-aquifer interaction is a key component of the hydrological cycle that affects water resources and quality. Recently, the application of...
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Comparison of tree-based ensemble learning algorithms for landslide susceptibility map** in Murgul (Artvin), Turkey
Turkey’s Artvin province is prone to landslides due to its geological structure, rugged topography, and climatic characteristics with intense...
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A Machine Learning (ML)-Based Approach to Improve Tropical Cyclone Intensity Prediction of NCMRWF Ensemble Prediction System
Global numerical weather prediction (NWP) models, including ensemble prediction systems (EPS), are routinely used by the forecasters to predict...
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LORA: a local ensemble transform Kalman filter-based ocean research analysis
We have produced an eddy-resolving local ensemble transform Kalman filter (LETKF)-based ocean research analysis (LORA) for the western North Pacific...
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Ensemble-based forecast sensitivity approach to estimate the impact of satellite-derived atmospheric motion vectors in a limited area model
Data impact studies have been conducted regularly to assess the value added by each observation type to the data assimilation (DA) systems in all the...
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Future Changes in Precipitation Over Northern Europe Based on a Multi-model Ensemble from CMIP6: Focus on Tana River Basin
Accurate climate projections help policymakers mitigate the negative effects of climatic changes and prioritize environmental issues based on...
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Map** the seamless hourly surface visibility in China: a real-time retrieval framework using a machine-learning-based stacked ensemble model
Surface visibility (SV), a key indicator of atmospheric transparency, is used widely in the fields of environmental monitoring, transportation, and...
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