Sensorless estimation of lake level by soft computing approach

Purpose The purpose of the paper is to evaluate a lake lavel prediction model. Lake-level prediction is very important task for different crucial issues like planning of water resource, controlled drainage, etc. Therefore, in this study, a soft computing approach was applied to predict the lake leve...

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Bibliographic Details
Published inSensor review Vol. 38; no. 1; pp. 117 - 119
Main Authors Jovic, Srdjan, Vasic, Predrag S, Jakšic, Tatjana R
Format Journal Article
LanguageEnglish
Published Bradford Emerald Publishing Limited 08.01.2018
Emerald Group Publishing Limited
Subjects
Creeks & streams
Datasets
Hydrology
Prediction models
Rivers
Soft computing
Support vector machines
Water resources
Serbia
Metrology
Agriculture
Soft computing
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Summary:Purpose The purpose of the paper is to evaluate a lake lavel prediction model. Lake-level prediction is very important task for different crucial issues like planning of water resource, controlled drainage, etc. Therefore, in this study, a soft computing approach was applied to predict the lake levels based on the different prediction horizons. Design/methodology/approach The main focus was to establish a sensorless estimation of the lake level based on different prediction horizons. Support vector regression approach was implemented for the lake-level prediction, as this approach is suitable for highly nonlinear prediction problems. Findings Ludoš Lake in Serbia was used for analysis. Originality/value According the results, the soft computing models can be used confidently for the lake-level prediction based on the prediction accuracy.
ISSN:0260-2288
1758-6828
DOI:10.1108/SR-07-2017-0138