Sensorless estimation of lake level by soft computing approach

Abstract

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.

Citation

Jovic, S., Vasic, P.S. and Jakšic, T.R. (2018), "Sensorless estimation of lake level by soft computing approach", Sensor Review, Vol. 38 No. 1, pp. 117-119. https://doi.org/10.1108/SR-07-2017-0138