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Outlier Detection and Correction for Monitoring Data of Water Quality Based on Improved VMD and LSSVM

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  • Guangpei Sun
  • Peng Jiang
  • Huan Xu
  • Shanen Yu
  • Dong Guo
  • Guang Lin
  • Hui Wu

Abstract

To improve the detection rate and reduce the correction error of abnormal data for water quality, an outlier detection and correction method is proposed based on the improved Variational Mode Decomposition (improved VMD) and Least Square Support Vector Machine (LSSVM) algorithms. The correlation coefficient is introduced, for solving the optimal parameter k of VMD algorithm, and an improved VMD algorithm is obtained. Combined with LSSVM algorithm, the outliers of water quality can be detected and repaired. This method is applied for the detection and correction of water quality monitoring outliers using dissolved oxygen which is retrieved from the water quality monitoring station in Hangzhou, Zhejiang Province, China. The result shows that the improved VMD algorithm is of higher detection rate and lower error rate than those of Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD). The LSSVM algorithm increases the fitting accuracy and decreases correction error in comparison with SVM and BP neural network, which provides important references for the implementation of environmental protection measures.

Suggested Citation

  • Guangpei Sun & Peng Jiang & Huan Xu & Shanen Yu & Dong Guo & Guang Lin & Hui Wu, 2019. "Outlier Detection and Correction for Monitoring Data of Water Quality Based on Improved VMD and LSSVM," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    • Handle: RePEc:hin:complx:9643921
    DOI: 10.1155/2019/9643921
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    References listed on IDEAS

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    1. Aldo M. Garay & Heleno Bolfarine & Victor H. Lachos & Celso R.B. Cabral, 2015. "Bayesian analysis of censored linear regression models with scale mixtures of normal distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2694-2714, December.
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    Cited by:

    1. Muhammad Izhar Shah & Taher Abunama & Muhammad Faisal Javed & Faizal Bux & Ali Aldrees & Muhammad Atiq Ur Rehman Tariq & Amir Mosavi, 2021. "Modeling Surface Water Quality Using the Adaptive Neuro-Fuzzy Inference System Aided by Input Optimization," Sustainability, MDPI, vol. 13(8), pages 1-17, April.

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