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- Title
Establishment of NH<sub>3</sub>-N Prediction Model in Aquaculture Water Based on ELMAN Neural Network.
- Authors
Wang Xiang; He Jixiang; She Lei; Zhang Jing
- Abstract
In the present study, ELMAN artificial neural network model was developed to predict the change of NH3-N in aquaculture wafer. The indexes including teed ration , dissolved oxygen in wafer , wafer temperature , air temperature , wafer turbidity , rainfall were recorded and chosen as the input variables , while the NH3-N content in the corresponding pond was chosen as output variable. The above data were collected evetyday from June to October in 2014 and were used to develop model in this test , and the data collected in November of 2014 were chosen to evaluate the developed model. The results showed that the changing trend of NH3-N in aquaculture wafer could be simulated well by the model , the predictive absolute error mean was 0.016 mg/L , and Nash-Sufcliffe efficiency coefficient was 0.74. The prediction model based on ELMAN neural network had a strong ability to describe the nonlinear dynamic changes of NH3-N content in aquaculture wafer , and if showed the good adaptability and accuracy in practical application.
- Subjects
AMMONIA; COMPOSITION of water; AQUACULTURE; TURBIDITY; PREDICTION models; ARTIFICIAL neural networks; DISSOLVED oxygen in water; NONLINEAR systems
- Publication
Meteorological & Environmental Research, 2015, Vol 6, Issue 10, p19
- ISSN
2152-3940
- Publication type
Article