A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
Biodiesel has been emerging as a potential and promising biofuel for the strategy of
reducing toxic emissions and improving engine performance. Computational methods …
reducing toxic emissions and improving engine performance. Computational methods …
A review of the artificial neural network models for water quality prediction
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
Machine learning methods for better water quality prediction
In any aquatic system analysis, the modelling water quality parameters are of considerable
significance. The traditional modelling methodologies are dependent on datasets that …
significance. The traditional modelling methodologies are dependent on datasets that …
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 …
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …
and management in both the short and long terms. Despite of some studies using machine …
[HTML][HTML] Exploding the myths: An introduction to artificial neural networks for prediction and forecasting
Abstract Artificial Neural Networks (ANNs), sometimes also called models for deep learning,
are used extensively for the prediction of a range of environmental variables. While the …
are used extensively for the prediction of a range of environmental variables. While the …
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions
The development and application of evolutionary algorithms (EAs) and other metaheuristics
for the optimisation of water resources systems has been an active research field for over …
for the optimisation of water resources systems has been an active research field for over …
Application of ANN technique to predict the performance of solar collector systems-A review
HK Ghritlahre, RK Prasad - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
The solar collector is the heart of any solar energy collection system designed for operation
in the low to medium temperature ranges. So, an efficient design of solar collector system …
in the low to medium temperature ranges. So, an efficient design of solar collector system …
Deep learning data-intelligence model based on adjusted forecasting window scale: application in daily streamflow simulation
Streamflow forecasting is essential for hydrological engineering. In accordance with the
advancement of computer aids in this field, various machine learning (ML) models have …
advancement of computer aids in this field, various machine learning (ML) models have …
Data-driven input variable selection for rainfall–runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines
Selecting an adequate set of inputs is a critical step for successful data-driven streamflow
prediction. In this study, we present a novel approach for Input Variable Selection (IVS) that …
prediction. In this study, we present a novel approach for Input Variable Selection (IVS) that …