An implementation of artificial neural reservoir computing technique for inflow forecasting of nagarjuna sagar dam

ISSN: 22773878
0Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

All over India flash flood or recurring flood is one of the major natural disaster causing life and economic threats. Several times a year, some or the other state disaster management in India have to face this. Forecasting system for inflow of any dam plays a key role in this disaster and its recovery. Current forecasting systems follow conventional, graphical metrological procedures and limited Artificial Neural Network models.This work provides novel model for forecasting inflow of a dam. Proposed model uses Neural Reservoir Computing for forecasting inflow. Forecasts are based on standard dam parameters like inflow. Most importantly, forecasts done are several days ahead of time. This would help disaster management systems to be prepared well in advance to save lives. Proposed system is demonstrated over data from two major dams in Andhra Pradesh. Results are compared with statistical forecasting models like AR, MA, & ARIMA and Artificial Neural Networks (ANN) model. Comparison prove proposed neural reservoir computing model to be better than existing systems.

Cite

CITATION STYLE

APA

Pradeepakumari, B., & Srinivasu, K. (2019). An implementation of artificial neural reservoir computing technique for inflow forecasting of nagarjuna sagar dam. International Journal of Recent Technology and Engineering, 8(1), 860–864.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free