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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.

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