Dam blocks movement prediction using artifical neural networks
Journal Title: Geodetski glasnik - Year 2017, Vol 51, Issue 48
Abstract
The dams are very important objects for production of electric energy, irrigation, flood management and tourism. However, besides all benefits the dams provide, they also represent great danger for areas downstream because there is always risk of dam failure. To prevent dam failure it is important to perform regular dam monitoring and for that purpose geodetic and physical methods are used. Geodetic methods use special network of points for object monitoring where reference points are used for monitoring of object points which are strategically distributed on the object. By quality prediction of object behavior it would be possible to prevent further damage on the object and additionally to save human lives in cases of great danger. In this paper artificial neural networks (ANNs) are used for dam movement prediction. ANNs are very popular tool for prediction since they are known for their quick learning ability and good generalization ability which gives them advantage compared to traditional statistical methods.
Authors and Affiliations
Hamzić Adis, Zikrija Avdagić
Keywords
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