Journal of Korean Society on Water Environment (한국물환경학회지)

Korean Society on Water Environment (한국물환경학회)
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Study on the Prediction of Daily TOC Data by Using Wavelet Transform and Artificial Neural Networks

웨이블렛 변환과 인공신경망을 이용한 일 TOC 자료의 예측에 관한 연구

  • Gwak, Pil Jeong (Department of Civil Engineering, Dongshin University) ;
  • Oh, Chang Ryol (Department of Civil Engineering, Dongshin University) ;
  • Jin, Young Hoon (Department of Civil Engineering, Dongshin University) ;
  • Park, Sung Chun (Department of Civil Engineering, Dongshin University)
  • 곽필정 (동신대학교 토목공학과) ;
  • 오창열 (동신대학교 토목공학과) ;
  • 진영훈 (동신대학교 토목공학과) ;
  • 박성천 (동신대학교 토목공학과)
  • Received : 2006.07.26
  • Accepted : 2006.08.28
  • Published : 2006.09.30
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Abstract

The present study applied wavelet transform and artificial neural networks (ANNs) for the prediction of daily TOC data. TOC data were transformed into denoised data by the wavelet transform and the noise-reduced data were used for the prediction model by artificial neural networks. For the application of wavelet transform, Daubechies wavelet of order 10 ('db10') was used as a basis function and decomposed the TOC data up to fifth level with five detail components and one approximation component. ANNs were calibrated with the input data of the segregated TOC data corresponding to the details from second to fifth level and the approximation. Consequently, the ANNs model for the prediction of daily TOC data showed the best result when it had seventeen hidden nodes in its layer.

Keywords

References

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