Environment and Ecology Research Vol. 10(2), pp. 218 - 224
DOI: 10.13189/eer.2022.100211
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Performance of Water Level Forecasting Based on Chaos Approach Using Data Splitting


Adib Mashuri 1, Nur Hamiza Adenan 2,*, Nor Suriya Abd Karim 2, Mohd Shahriman Adenan 3, Nurulhuda Che Abd Rani 4
1 Department of General Studies, Batu Lanchang Vocational College, 11600 Jelutong, Pulau Pinang, Malaysia
2 Department of Mathematics, Faculty Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak, Malaysia
3 School of Mechanical Engineering, College of Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
4 Department of Mathematics, Science and Computer, Politeknik Sultan Abdul Halim Muā€™adzam Shah, 06900 Jitra, Kedah, Malaysia

ABSTRACT

Forecasting accuracy should be prioritised in flood plain areas. This research focuses on data split of water level time series datasets in producing excellent forecasts as measured by coefficient correlation (CC). The datasets involved 6000 hours chosen from a recent research location at Sungai Dungun water level, which the data was split into different ratio datasets (50:50, 60:40, 70:30, 80:20, 90:10). A recent study has proved that the chaotic dynamic existed in time series data when running the data using the Cao method. The dataset used was divided into training and testing data to evaluate the performance based on the local linear approximation method. Those sets of data required a combination of parameters for prediction. In this study, the data split of water level time series data gave impacts to the combination of parameters for prediction. The result obtained was in the range of strong forecast using chaos approach with over 95% accuracy in every dataset. In addition, the dataset with a 50:50 ratio showed the highest CC obtained, and its values decreased in ascending order of 60:40, 70:30, 80:20, and 90:10. It showed that the splitting data of training and testing had an impact on prediction results. The higher number of training data ran, the lower number of CC was obtained. However, the chaos method still gives excellent prediction results, even when forecasting using different ratios of data set.

KEYWORDS
Data Splitting, Different Ratio, Water Level, Chaos Approach, Prediction

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Adib Mashuri , Nur Hamiza Adenan , Nor Suriya Abd Karim , Mohd Shahriman Adenan , Nurulhuda Che Abd Rani , "Performance of Water Level Forecasting Based on Chaos Approach Using Data Splitting," Environment and Ecology Research, Vol. 10, No. 2, pp. 218 - 224, 2022. DOI: 10.13189/eer.2022.100211.

(b). APA Format:
Adib Mashuri , Nur Hamiza Adenan , Nor Suriya Abd Karim , Mohd Shahriman Adenan , Nurulhuda Che Abd Rani (2022). Performance of Water Level Forecasting Based on Chaos Approach Using Data Splitting. Environment and Ecology Research, 10(2), 218 - 224. DOI: 10.13189/eer.2022.100211.