scholarly journals Eutrophication forecasting and management by artificial neural network: a case study at Yuqiao Reservoir in North China

2015 ◽  
Vol 17 (4) ◽  
pp. 679-695 ◽  
Author(s):  
Ya Zhang ◽  
Jinhui Jeanne Huang ◽  
Liang Chen ◽  
Lan Qi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Water Temperature ◽  
Chlorophyll A ◽  
Total Phosphorus ◽  
Ann Model ◽  
Validation Data ◽  
Yuqiao Reservoir ◽  
Artificial Neural ◽  
Sound Management

Yuqiao Reservoir is the potable water supply source for a city with a population of more than 14 million. Eutrophication has threatened the reliability of drinking water supplies and, therefore, the forecasting systems for eutrophication and sound management become urgent needs. Water temperature and total phosphorus have long been considered as the major influencing factors to eutrophication. This study used the artificial neural network (ANN) model to forecast three water quality variables including water temperature, total phosphorus, and chlorophyll-a in Yuqiao Reservoir. Two weeks in advance for forecasting was chosen to ensure a sufficient preparation response time for algae outbreak. The Nash–Sutcliffe coefficient of efficiency (R2) was between 0.84 and 0.99 for the training and over-fitting test data sets, while it was between 0.59 and 0.99 for the validation data set. To better respond to the algae outbreak, a number of management scenarios formed by orthogonal experimental design were modeled to assess the responses of chlorophyll-a and an optimal management scenario was identified, which can reduce chlorophyll-a by 23.8%. This study demonstrates that ANN model is potentially useful for forecasting eutrophication up to 2 weeks in advance. It also provides valuable information for the sound management of nutrient loads to reservoirs.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural

Forecasting travel demand: a comparison of logit and artificial neural network methods

1998 ◽  
Vol 49 (7) ◽  
pp. 717-722 ◽  
Author(s):  
M C M de Carvalho ◽  
M S Dougherty ◽  
A S Fowkes ◽  
M R Wardman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Travel Demand ◽  
Network Methods ◽  
Artificial Neural

An Artificial Neural Network to Evaluate Cartilage Collagen and Proteoglycan Fractions Based on Multiparametric Quantitative MRI Techniques

2019 ◽  
Author(s):  
Johannes Thüring ◽  
Kevin Linka ◽  
Christiane Kuhl ◽  
Sven Nebelung ◽  
Daniel Truhn
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Quantitative Mri ◽  
Artificial Neural
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