The week's pick
Reseach Article
Assessing Search and Rescue Optimization based DNN Model for Streamflow Data Prediction
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 19 |
| Year of Publication: 2021 |
| Authors: Syed H. Hasan, Syeda Huyam Hasan, Syed Hamid Hasan, Salman Khalid |
10.5120/ijca2021921493
|
Syed H. Hasan, Syeda Huyam Hasan, Syed Hamid Hasan, Salman Khalid . Assessing Search and Rescue Optimization based DNN Model for Streamflow Data Prediction. International Journal of Computer Applications. 183, 19 ( Aug 2021), 11-16. DOI=10.5120/ijca2021921493
Abstract
For many activities related to water resource management, such as flood and drought control, reservoir service, water supply planning and hydroelectric power generation, accurate streamflow prediction is important. While both short- and long-term forecasts are important, reservoir activities are usually planned on the basis of monthly periods; monthly streamflow forecasts therefore play a major role in the management of water resources. Therefore, there is need to propose an efficient approach for prediction of streamflow to improve the system efficiency. Hence, in this paper we have developed an adaptive model based on Search and rescue optimization based DNN for prediction of monthly streamflow. The analysis shows that the adaptive model outperforms existing models such as ANN, SVM and OANN. This AI based learning model shows that this model can able to handle huge number of data for prediction of monthly inflow.
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