Csábrági, Anita and Molnár, Sándor and Tanos, P. and Kovács, J. (2015) FORECASTING OF DISSOLVED OXYGEN IN THE RIVER DANUBE USING NEURAL NETWORKS. HUNGARIAN AGRICULTURAL ENGINEERING (27). pp. 38-41. ISSN 0864-7410
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Abstract
The Danube is the second-largest river in Europe and the conservation of its water quality is very important because it influences the lives of millions people. The aim of this research is to predict one of the most important water quality parameters, dissolved oxygen, with the help of water pH, runoff, water temperature and electrical conductivity data. Multivariate Linear Regression (MLR), Back-propagation Neural Networks (BPNN) and General Regression Neural Networks (GRNN) were applied and their performances compared in this study. The most accurate prediction proved to be GRNN. This paper describes the influence of single input parameters on the prediction.
| Item Type: | Article |
|---|---|
| Subjects: | S Agriculture / mezőgazdaság > S1 Agriculture (General) / mezőgazdaság általában T Technology / alkalmazott, műszaki tudományok > TA Engineering (General). Civil engineering (General) / általános mérnöki tudományok |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 15 Feb 2016 15:21 |
| Last Modified: | 15 Feb 2016 15:21 |
| URI: | http://real.mtak.hu/id/eprint/33508 |
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