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Abstract

Fuzzy weighted multivariate regression analysis is proposing to assess the water pollution based on water quality index (WQI). In this research the data used to test the performance of the proposed approach were collected from several locations of Perak River at Perak State, Malaysia. The water quality index was monitored during the year 2013–2017. The water quality index (WQI) are express water quality by integrating measurements of six (6) selected water quality parameters is pH, chemical oxygen demand, ammoniacal nitrogen, dissolved oxygen, suspended solid and biochemical oxygen demand (BOD). The index was developed for the purpose of providing a simple, concise and valid method for expressing the significance of regularly generated laboratory data and water quality for compliance with the Standards adopted for 6 designated classes of beneficial uses. The WQI provides a basis to evaluate effectiveness of water quality improvement and assist in establishing priorities for management purpose even though it is not meant specifically as an absolute measure of the degree of pollutant or the actual water quality. A fuzzy Logic approach has shown to be practical, simple and useful tool to assess the water pollution levels. The proposed in this study is we create new model of WQI according to the standard prepared by Department of Environmental (DOE), Malaysia—involving all six parameters. The main difference is the model that we are proposing. The expected results are: (a) Relationships between all six parameters with WQI (b) New Fuzzy based on multivariate regression analysis to be developed that will outperform some existing at Perak River or other river in Malaysia and Indonesia. The model is line with the National Water Quality Standards for Malaysia.

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References

  1. L. Abdullah, N. Zakaria, Matrix driven multivariate fuzzy linear regression model in car sales. J. Appl. Sci. 12, 56–63 (2012)

    Article  Google Scholar 

  2. ASMA.: River Water Quality Monitoring (2012). http://www.doe.gov.my/portalv1/en/general-info/pemantauan-kualiti-air-sungai/280 retrieved from 13 May 2019

  3. A.A.A. Bakar, A.M. Pauzi, A.A. Mohamed, S.S. Sharifuddin, F.M. Idris, Preliminary analysis on the water quality index (WQI) of irradiated basic filter elements, in IOP Conference Series: Material Science and Engineering, vol. 298, 012005 (2018)

    Article  Google Scholar 

  4. L.W. Canter, Environmental Impact of Water Resources Projects (Lewis Publishers, Inc. Chelsea, 1985)

    Google Scholar 

  5. P.T. Chang, E.S. Lee, A generalized fuzzy weighted least-squares regression. Fuzzy Sets Syst. 82, 289–298 (1996)

    Article  MathSciNet  Google Scholar 

  6. P. D’Urso, T. Gastaldi, A least-squares approach to fuzzy linear regression analysis. Comput. Stat. Data Anal. 34, 427–440 (2000)

    Article  Google Scholar 

  7. P. D’Urso, T. Gastaldi, Linear fuzzy regression analysis with asymmetric spreads, in Advances in Data Science and Classification, ed. by S. Borra, R. Rocci, M. Vichi, M. Schader (Springer, Heidelberg, 2001), pp. 257–264

    Chapter  Google Scholar 

  8. B. Heshmati, A. Kandel, Fuzzy linear regression and its application to forecasting in uncertain environment. Fuzzy Set Syst. 15, 159–191 (1985)

    Article  Google Scholar 

  9. R.K. Horton, An index number system for rating water quality. J. Water Pollut. Control Fed. 37(3), 300–305 (1965)

    Google Scholar 

  10. N.H.M. Isa, M. Othman, S.A.A. Karim, Multivariate matrix for fuzzy linear regression model to analyze the taxation in Malaysia. Int. J. Eng. Technol. 7(4.33), 78–82 (2018)

    Google Scholar 

  11. L.Y. Khuan, N. Hamzah, R. Jailani, Prediction of water quality index (WQI) based on artificial neural network (ANN), in 2002 Student Conference on Research and Development Proceedings (Shah Alam, Malaysia, 2002), pp. 157–161

    Google Scholar 

  12. A.A. Mamun, S.N. Hafizah, M.Z. Alam, Improvement of existing water quality index in Selangor, Malaysia, in 2nd International Conference on Water & Flood Management (ICWFM), 15–17 Mar. 09, Dhaka, Bangladesh (2009)

    Google Scholar 

  13. W.R. Ott, Water Quality Indices: A Survey of Indices Used in the United States, EPA-600/4-78-005 (US Environmental Protection Agency, Washington, 1978), pp. 128

    Google Scholar 

  14. N.F. Pan, T.C. Lin, N.H. Pan, Estimating bridge performance based on a matrix-driven fuzzy linear regression model. Autom. Constr. 18, 578–586 (2009). https://doi.org/10.1016/j.autcon.2008.12.005

    Article  Google Scholar 

  15. H.I. Sii, J.H. Sherrard, T.E. Wilson, A water quality index based on fuzzy sets theory, in Proceedings of the 1993 Joint ASCE-CSCE National Conference on Environmental Engineering, July 12–14, Montreal, Quebec, Canada (1993), pp. 253–259

    Google Scholar 

  16. H. Tanaka, S. Uejima, K. Asai, Linear regression analysis with fuzzy model. IEEE Trans. Syst. Man Cybern. 12(6), 903–907 (1982)

    Google Scholar 

  17. L.A. Zadeh, Fuzzy set. Inform. Control 8, 338–353 (1965)

    Google Scholar 

  18. N.S. Zainordin, N.A. Ramli, M. Elbayoumi, Distribution and temporal behavior of O3 and NO2 near selected schools in Seberang Perai, Pulau Pinang and Parit Buntar, Perak. Malaysia. Sains Malaysiana 46(2), 197–207 (2017)

    Article  Google Scholar 

Download references

Acknowledgements

This study is fully supported by Universitas Islam Riau (UIR), Pekan baru, Indonesia and Universiti Teknologi PETRONAS (UTP), Malaysia through International Collaborative Research Funding (ICRF): 015ME0-037. The first author is currently doing his internship at UTP under Research Attachment Program (RAP).

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Correspondence to Samsul Ariffin Abdul Karim .

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Yasin, M.I., Karim, S.A.A. (2020). A New Fuzzy Weighted Multivariate Regression to Predict Water Quality Index at Perak Rivers. In: Karim, S., Kadir, E., Nasution, A. (eds) Optimization Based Model Using Fuzzy and Other Statistical Techniques Towards Environmental Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-15-2655-8_1

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