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Neural Computing and Applications

, Volume 31, Issue 12, pp 8463–8473 | Cite as

Neuro-fuzzy-wavelet hybrid approach to estimate the future trends of river water quality

  • Kulwinder Singh ParmarEmail author
  • Sidhu Jitendra Singh Makkhan
  • Sachin Kaushal
Original Article
  • 14 Downloads

Abstract

Water is the basic need for life to exist on this planet earth; rivers play a vital role to fulfill this need for the supply of freshwater. Due to spontaneous growth of industrialization and urbanization near the important rivers, most of them have been polluted to a severe extent and the future of these rivers and living organism depending on the water from them is on threat. Thus, various prediction models have been developed by researchers to build an accurate forecasting model to access the future quality of rivers with least forecasting error. Time series models have been developed to form such prediction, but most of them were unsuccessful in handling nonlinear problems. Artificial neural network (ANN) and adaptive neuro-fuzzy interface system have proven to be an efficient tool to handle such nonlinear situations. In this study, in addition to the above methods, wavelet transformation has been used to develop a forecasting model to generate forecasts close to actual values. The biochemical oxygen demand of river Yamuna at sample site of Nizamuddin (Delhi) is predicted using the past monthly averaged data. Statistical analysis has been used to study the nature of the wavelet domain constitutive series considered. The results obtained indicate that the neuro-fuzzy-wavelet-coupled model leads to considerably superior outcomes compared to neuro-fuzzy, ANN and regression models.

Keywords

Hydrological model River water management Neural network Fuzzy logic Wavelets Mathematical modeling 

Notes

Acknowledgements

First author is thankful to Prof (Dr.) Rashmi Bhardwaj, Department of Mathematics, Guru Gobind Singh Indraprastha University, New Delhi for providing guidance at each step with special thanks to Central Pollution Control Board (CPCB), Government of India for providing the research data; IKG Punjab Technical University, Jalandhar (Punjab), India for providing the necessary research facilities.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of MathematicsI K Gujral Punjab Technical UniversityJalandharIndia
  2. 2.Department of Mathematics, School of Chemical Engineering and Physical SciencesLovely Professional UniversityPhagwaraIndia
  3. 3.Department of MathematicsSri Guru Angad Dev CollegeTarn TaranIndia

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