A brief review of random forests for water scientists and practitioners and their recent history in water resources
Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …
to gain prominence in water resources applications. However, existing applications are …
A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
The main purpose of the present study is to use three state-of-the-art data mining
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …
Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management
W Niu, Z Feng - Sustainable Cities and Society, 2021 - Elsevier
Accurate runoff forecasting plays an important role in guaranteeing the sustainable
utilization and management of water resources. Artificial intelligence methods can provide …
utilization and management of water resources. Artificial intelligence methods can provide …
Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm
Reservoirs and dams are vital human-built infrastructures that play essential roles in flood
control, hydroelectric power generation, water supply, navigation, and other functions. The …
control, hydroelectric power generation, water supply, navigation, and other functions. The …
Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization
Z Feng, W Niu, Z Tang, Z Jiang, Y Xu, Y Liu… - Journal of Hydrology, 2020 - Elsevier
Accurate monthly runoff prediction plays an important role in the planning and management
of water resources. However, owing to climate changes and human activities, natural runoff …
of water resources. However, owing to climate changes and human activities, natural runoff …
Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information
T Yang, AA Asanjan, E Welles, X Gao… - Water Resources …, 2017 - Wiley Online Library
Reservoirs are fundamental human‐built infrastructures that collect, store, and deliver fresh
surface water in a timely manner for many purposes. Efficient reservoir operation requires …
surface water in a timely manner for many purposes. Efficient reservoir operation requires …
A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data
Physically distributed hydrological models are effective in hydrological simulations of large
river basins, but the complex characteristics of hydrological features limit their application …
river basins, but the complex characteristics of hydrological features limit their application …
Real-time reservoir operation using recurrent neural networks and inflow forecast from a distributed hydrological model
Large-scale reservoirs play an essential role in water resources management for agriculture
irrigation, water supply and flood controls. However, we need robust reservoir operation …
irrigation, water supply and flood controls. However, we need robust reservoir operation …
Training machine learning surrogate models from a high‐fidelity physics‐based model: Application for real‐time street‐scale flood prediction in an urban coastal …
Mitigating the adverse impacts caused by increasing flood risks in urban coastal
communities requires effective flood prediction for prompt action. Typically, physics‐based 1 …
communities requires effective flood prediction for prompt action. Typically, physics‐based 1 …
Water level forecasting using deep learning time-series analysis: A case study of red river of the north
The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …