Protocol for developing 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 …
[图书][B] Coagulation and flocculation in water and wastewater treatment
J Bratby - 2016 - books.google.com
Coagulation and Flocculation in Water and Wastewater Treatment provides a
comprehensive account of coagulation and flocculation techniques and technologies in a …
comprehensive account of coagulation and flocculation techniques and technologies in a …
Input determination for neural network models in water resources applications. Part 1—background and methodology
The use of artificial neural network (ANN) models in water resources applications has grown
considerably over the last decade. However, an important step in the ANN modelling …
considerably over the last decade. However, an important step in the ANN modelling …
Using artificial neural network for reservoir eutrophication prediction
JT Kuo, MH Hsieh, WS Lung, N She - Ecological modelling, 2007 - Elsevier
Reservoirs provide approximately 70% of water supply for domestic and industrial use in
Taiwan. The water quality of reservoirs is now one of the key factors in the operation and …
Taiwan. The water quality of reservoirs is now one of the key factors in the operation and …
[图书][B] Neural networks for hydrological modeling
A new approach to the fast-developing world of neural hydrological modelling, this book is
essential reading for academics and researchers in the fields of water sciences, civil …
essential reading for academics and researchers in the fields of water sciences, civil …
Choice of rainfall inputs for event-based rainfall-runoff modeling in a catchment with multiple rainfall stations using data-driven techniques
Input selection for data-driven rainfall-runoff models is an important task as these models
find the relationship between rainfall and runoff by direct mapping of inputs to output. In this …
find the relationship between rainfall and runoff by direct mapping of inputs to output. In this …
Urban water interfaces
MO Gessner, R Hinkelmann, G Nützmann, M Jekel… - Journal of …, 2014 - Elsevier
Urban water systems consist of large-scale technical systems and both natural and man-
made water bodies. The technical systems are essential components of urban infrastructure …
made water bodies. The technical systems are essential components of urban infrastructure …
Rainfall-runoff modelling using a self-reliant fuzzy inference network with flexible structure
Conventional neuro-fuzzy systems used for rainfall-runoff (RR) modelling are generally
dependent on expert knowledge. In these models, not only the structure is designed by the …
dependent on expert knowledge. In these models, not only the structure is designed by the …
Artificial neural network modelling: a summary of successful applications relative to microbial water quality
GM Brion, S Lingireddy - Water science and technology, 2003 - iwaponline.com
Artificial neural networks (ANN) are modelling tools that can be of great utility in studies of
microbial water quality. The ability of ANNs to work with complex, inter-related …
microbial water quality. The ability of ANNs to work with complex, inter-related …
A neural-network-based classification scheme for sorting sources and ages of fecal contamination in water
GM Brion, TR Neelakantan, S Lingireddy - Water research, 2002 - Elsevier
Artificial neural networks (ANNs) were successfully applied to data observations from a
small watershed consisting of commonly measured indicator bacteria, weather conditions …
small watershed consisting of commonly measured indicator bacteria, weather conditions …