Abstract:
In this work, the reservoir water level has been
predicted using one of the soft computing techniques named
Artificial Neural Network. The reservoir water level is influenced
by many parameters. Among which the most influencing
parameters have been considered here: amount of rainfall,
temperature and evaporation. For this analysis, the reservoir
made on Shetrunji River Dam in Dhari, Amreli district, Gujarat,
India has been chosen as it was overflown seven times in last ten
years. This shows the importance of water level prediction at this
particular reservoir. The Neural Network is trained using the past
data collected and further used to predict water level for the
unknown data. The approach of the multiple regression is also
shown for its comparison with the Soft computing approach.
Computations and experimental works were done by
programming in software MATLAB. Such modeling is useful for
planning and decision making of opening gates for reservoir
operation particularly during monsoon and water scarcity
Description:
International Journal of Soft Computing and Engineering (IJSCE)
ISSN: 2231-2307, Volume-6 Issue-3, July 2016, P. 55-59