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Assessing Search and Rescue Optimization based DNN Model for Streamflow Data Prediction

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Syed H. Hasan, Syeda Huyam Hasan, Syed Hamid Hasan, Salman Khalid

Syed H Hasan, Syeda Huyam Hasan, Syed Hamid Hasan and Salman Khalid. Assessing Search and Rescue Optimization based DNN Model for Streamflow Data Prediction. International Journal of Computer Applications 183(19):11-16, August 2021. BibTeX

	author = {Syed H. Hasan and Syeda Huyam Hasan and Syed Hamid Hasan and Salman Khalid},
	title = {Assessing Search and Rescue Optimization based DNN Model for Streamflow Data Prediction},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2021},
	volume = {183},
	number = {19},
	month = {Aug},
	year = {2021},
	issn = {0975-8887},
	pages = {11-16},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2021921493},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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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Data prediction, Deep Neural Network, Streamflow, Optimization, and monthly inflow