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 …
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
Over the past 15 years, artificial neural networks (ANNs) have been used increasingly for
prediction and forecasting in water resources and environmental engineering. However …
prediction and forecasting in water resources and environmental engineering. However …
[LIVRE][B] Rainfall-runoff modelling: the primer
KJ Beven - 2012 - books.google.com
Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and
authoritative text, first published in 2001. The book provides both a primer for the novice and …
authoritative text, first published in 2001. The book provides both a primer for the novice and …
[PDF][PDF] Catchment scale hydrological modelling: A review of model types, calibration approaches and uncertainty analysis methods in the context of recent …
In catchment hydrology, it is in practice impossible to measure everything we would like to
know about the hydrological system, mainly due to high catchment heterogeneity and the …
know about the hydrological system, mainly due to high catchment heterogeneity and the …
Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds
In the past decade, machine learning methods for empirical rainfall–runoff modeling have
seen extensive development and been proposed as a useful complement to physical …
seen extensive development and been proposed as a useful complement to physical …
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 …
Two hybrid artificial intelligence approaches for modeling rainfall–runoff process
The need for accurate modeling of the rainfall–runoff process has grown rapidly in the past
decades. However, considering the high stochastic property of the process, many models …
decades. However, considering the high stochastic property of the process, many models …
Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model
The applicability of four machine learning (ML) methods, ANFIS-PSO, ANFIS-FCM, MARS
and M5Tree, together with multi model simple averaging (MM-SA) ensemble method, is …
and M5Tree, together with multi model simple averaging (MM-SA) ensemble method, is …
Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
This paper traces two decades of neural network rainfall-runoff and streamflow modelling,
collectively termed 'river forecasting'. The field is now firmly established and the research …
collectively termed 'river forecasting'. The field is now firmly established and the research …
Neural network river forecasting through baseflow separation and binary-coded swarm optimization
The inclusion of expert knowledge in data-driven streamflow modeling is expected to yield
more accurate estimates of river quantities. Modular models (MMs) designed to work on …
more accurate estimates of river quantities. Modular models (MMs) designed to work on …