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 …
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 …
Projection-based model reduction: Formulations for physics-based machine learning
This paper considers the creation of parametric surrogate models for applications in science
and engineering where the goal is to predict high-dimensional output quantities of interest …
and engineering where the goal is to predict high-dimensional output quantities of interest …
A state‐of‐the‐art review of optimal reservoir control for managing conflicting demands in a changing world
The state of the art for optimal water reservoir operations is rapidly evolving, driven by
emerging societal challenges. Changing values for balancing environmental resources …
emerging societal challenges. Changing values for balancing environmental resources …
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 …
Protocol for develo** ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling
Abstract The application of Artificial Neural Networks (ANNs) in the field of environmental
and water resources modelling has become increasingly popular since early 1990s. Despite …
and water resources modelling has become increasingly popular since early 1990s. Despite …
Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers
Groundwater is the most important water resource in semi-arid and arid regions such as
Iran. It is necessary to study groundwater level fluctuations to manage disasters (such as …
Iran. It is necessary to study groundwater level fluctuations to manage disasters (such as …
An evaluation framework for input variable selection algorithms for environmental data-driven models
Abstract Input Variable Selection (IVS) is an essential step in the development of data-driven
models and is particularly relevant in environmental modelling. While new methods for …
models and is particularly relevant in environmental modelling. While new methods for …
Comparison of self-organizing map, artificial neural network, and co-active neuro-fuzzy inference system methods in simulating groundwater quality: geospatial …
Water quality experiments are difficult, costly, and time-consuming. Therefore, different
modeling methods can be used as an alternative for these experiments. To achieve the …
modeling methods can be used as an alternative for these experiments. To achieve the …
Prediction of monthly regional groundwater levels through hybrid soft-computing techniques
Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial
patterns, which cause great difficulty in quantifying their complex processes, while reliable …
patterns, which cause great difficulty in quantifying their complex processes, while reliable …