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Introduction

Chapter
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Part of the SpringerBriefs in Water Science and Technology book series (BRIEFSWATER)

Abstract

This chapter discuss the introduction on the subject matter including some related literature reviews as well as the motivation of the study. The background of the study is presented in details.

Keywords

Water quality Fuzzy Crisp Fuzzy regression River 

References

  1. 1.
    Abdullah L, Zakaria N (2012) Matrix driven multivariate fuzzy linear regression model in car sales. J Appl Sci (Faisalabad) 12(1):56–63Google Scholar
  2. 2.
    Ahmad F, Yahaya S (2017) First-order interaction multiple regressions model on water quality index in Manjung River and its tributariesGoogle Scholar
  3. 3.
    Asadollahfardi G (2015) Water quality management: assessment and interpretation. Springer, BerlinGoogle Scholar
  4. 4.
    Asai HTSUK, Tanaka S, Uegima K (1982) Linear regression analysis with fuzzy model. IEEE Trans. Systems Man Cybern 12:903–907Google Scholar
  5. 5.
    Bakar AAA, Pauzi AM, Mohamed AA, Sharifuddin SS, Idris FM (2018) Preliminary analysis on the water quality index (WQI) of irradiated basic filter elements. In: IOP conference series: materials science and engineering, vol 298, no 1. IOP Publishing, p 012005Google Scholar
  6. 6.
    Bhavyashree S, Mishra M, Girisha GC (2017) Fuzzy regression and multiple linear regression models for predicting mulberry leaf yield: a comparative study. Int J Agric Stat Sci 13(1):149–152Google Scholar
  7. 7.
    Boyd CE (2020) Water quality: an introduction, 2nd edn. Springer, BerlinGoogle Scholar
  8. 8.
    Brown RM, McClelland NI, Deininger RA, Tozer RG (1970) A water quality index—do we dareGoogle Scholar
  9. 9.
    Canter LW (2018) Environmental impact of water resource projects. CRC PressGoogle Scholar
  10. 10.
    Chang PT, Lee ES (1996) A generalized fuzzy weighted least-squares regression. Fuzzy Sets Syst 82(3):289–298Google Scholar
  11. 11.
    Chen YS (2001) Outliers detection and confidence interval modification in fuzzy regression. Fuzzy Sets Syst 119(2):259–272Google Scholar
  12. 12.
    Choi SH, Buckley JJ (2008) Fuzzy regression using least absolute deviation estimators. Soft Comput 12(3):257–263Google Scholar
  13. 13.
    Cude CG (2001) Oregon water quality index a tool for evaluating water quality management effectiveness 1. JAWRA J Am Water Resour Assoc 37(1):125–137Google Scholar
  14. 14.
    Dinius SH (1987) Design of an index of water quality 1. JAWRA J Am Water Resour Assoc 23(5):833–843Google Scholar
  15. 15.
    D’Urso P, Gastaldi T (2000) A least-squares approach to fuzzy linear regression analysis. Comput Stat Data Anal 34(4):427–440Google Scholar
  16. 16.
    D’Urso P, Gastaldi T (2001) Linear fuzzy regression analysis with asymmetric spreads. In: Advances in classification and data analysis. Springer, Berlin, Heidelberg, pp 257–264Google Scholar
  17. 17.
    Dojlido J, Raniszewski J, Woyciechowska J (1994) Water quality index applied to rivers in the Vistula river basin in Poland. Environ Monit Assess 33(1):33–42Google Scholar
  18. 18.
    Duca G (2014) Management of water quality in Moldova. Springer International Publishing, ChamGoogle Scholar
  19. 19.
    Hidayah Mohamed Isa N, Othman M, Karim SAA (2018) Multivariate matrix for fuzzy linear regression model to analyse the taxation in Malaysia. Int J Eng Technol 7(4.33):78–82. http://dx.doi.org/10.14419/ijet.v7i4.33.23490
  20. 20.
    Horton RK (1965) An index number system for rating water quality. J Water Pollut Control Fed 37(3):300–306Google Scholar
  21. 21.
    Krätschmer V (2006) Least-squares estimation in linear regression models with vague concepts. Fuzzy Sets Syst 157(19):2579–2592Google Scholar
  22. 22.
    Kung HT, Ying LG, Liu YC (1992) A complementary tool to water quality index: fuzzy clustering analysis 1. JAWRA J Am Water Resour Assoc 28(3):525–533Google Scholar
  23. 23.
    Landwehr, J. M., & Deininger, R. A. (1976). A comparison of several water quality indexes. Journal (Water Pollution Control Federation), 954–958Google Scholar
  24. 24.
    Li Y, Nzudie HLF, Zhao X, Wang H (2020) Addressing the uneven distribution of water quantity and quality endowment: physical and virtual water transfer within China. In: SpringerBriefs in water science and technology. Springer, Singapore Google Scholar
  25. 25.
    Marcello B, George T (2013) Water quality modelling for rivers and streams. Springer, Water Science and Technology LibraryGoogle Scholar
  26. 26.
    Mohammadpour R, Shaharuddin S, Chang CK, Zakaria NA, Ab Ghani A, Chan NW (2015) Prediction of water quality index in constructed wetlands using support vector machine. Environ Sci Pollut Res 22(8):6208–6219Google Scholar
  27. 27.
    Ott W (1978) Water quality indices: a survey of indices used in the United States, vol 1. Environmental Protection Agency, Office of Research and Development, Office of Monitoring and Technical SupportGoogle Scholar
  28. 28.
    Pan NF, Lin TC, Pan NH (2009) Estimating bridge performance based on a matrix-driven fuzzy linear regression model. Autom Constr 18(5):578–586Google Scholar
  29. 29.
    Sakawa M, Yano H (1992) Multiobjective fuzzy linear regression analysis for fuzzy input-output data. Fuzzy Sets Syst 47(2):173–181Google Scholar
  30. 30.
    Sii HI, Sherrard JH, Wilson TE (1993) A water quality index based on fuzzy set theory. In: Environmental engineering-conference. American Society of Civil Engineers, pp 1727–1727Google Scholar
  31. 31.
    Sousa SIV, Martins FG, Pereira MC, Alvim-Ferraz MCM, Ribeiro H, Oliveira M, Abreu I (2010) Use of multiple linear regressions to evaluate the influence of O3 and PM10 on biological pollutants. Int J Environ Sci Eng 2(2):107–112Google Scholar
  32. 32.
    Tsuzuki Y (2014) Pollutant discharge and water quality in urbanisation. In: SpringerBriefs in water science and technology. Springer International Publishing, ChamGoogle Scholar
  33. 33.
  34. 34.
    Wu HC (2003) Fuzzy estimates of regression parameters in linear regression models for imprecise input and output data. Comput Stat Data Anal 42(1–2):203–217Google Scholar
  35. 35.
    Xu R, Li C (2001) Multidimensional least-squares fitting with a fuzzy model. Fuzzy Sets Syst 119(2):215–223Google Scholar
  36. 36.
    Yen J, Langari R (1999) Fuzzy logic: intelligence, control, and information, vol 1. Prentice Hall, Upper Saddle River, NJGoogle Scholar
  37. 37.
    Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353Google Scholar
  38. 38.
    Zainordin NS, Ramli NA, Elbayoumi M (2017) Distribution and temporal behaviour of O3 and NO2 near selected schools in Seberang Perai, Pulau Pinang and Parit Buntar, Perak, Malaysia. Sains Malays 46(2):197–207Google Scholar
  39. 39.
    Zali MA, Retnam A, Juahir H, Zain SM, Kasim MF, Abdullah B, Saadudin SB (2011) Sensitivity analysis for water quality index (WQI) prediction for Kinta River, Malaysia. World Appl Sci J 14:60–65Google Scholar

Copyright information

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Fundamental and Applied Sciences Department and Centre for Smart Grid Energy Research (CSMER), Institute of Autonomous SystemUniversiti Teknologi PETRONASSeri IskandarMalaysia
  2. 2.Fundamental and Applied Sciences DepartmentUniversiti Teknologi PETRONASSeri IskandarMalaysia

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