Open Access
Issue
E3S Web Conf.
Volume 158, 2020
2019 7th International Conference on Environment Pollution and Prevention (ICEPP 2019)
Article Number 05002
Number of page(s) 7
Section Environmental Detection
DOI https://doi.org/10.1051/e3sconf/202015805002
Published online 23 March 2020
  1. Edition F 2011 Guidelines for drinking-water quality WHO chronicle 38(4) 104. [PubMed] [Google Scholar]
  2. Payus C., Haziqah N., Basri N., and Wan V.L 2018 Faecal bacteria contaminations in untreated drinking water (Groundwater Well and Hill Water) from Rural Community Areas 215. [Google Scholar]
  3. Diarrhoeal disease World Health Organization 2017 Available Online at http://www.who.int/mediacentre/factsheets/fs330/en. [Google Scholar]
  4. Cabral J.P.S 2010 Water microbiology Bacterial pathogens and water International Journal of Environmental Research and Public Health 7 3657. [Google Scholar]
  5. Payment P., Richardson L., Siemiatycki J., Dewar R., Edwardes M and Franco E 1991 A randomized trial to evaluate the risk of gastrointestinal disease due to consumption of drinking water meeting current microbiological standards American journal of public health 81(6) 703. [CrossRef] [PubMed] [Google Scholar]
  6. Indian standard drinking water specification (Second Revision) IS 10500:2012. [Google Scholar]
  7. Negnevitsky M 2005 Artificial intelligence: a guide to intelligent systems. Pearson education. [Google Scholar]
  8. Bouharati S., Benmahammed K., Harzallah D and El-Assaf YM 2008 Application of artificial neuro-fuzzy logic inference system for predicting the microbiological pollution in fresh water Journal of Applied Sciences 8(2) 309. [CrossRef] [Google Scholar]
  9. Okwu MO, & Adetunji O 2018 A comparative study of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models in distribution system with nondeterministic inputs International Journal of Engineering Business Management 10 1847979018768421. [Google Scholar]
  10. Keshavarz Z and Torkian H 2018 Application of ANN and ANFIS models in determining compressive strength of concrete Soft Computing in Civil Engineering 2(1) 62. [Google Scholar]
  11. Calp MH 2019 A Hybrid ANFIS-GA Approach for Estimation of Regional Rainfall Amount. Gazi University Journal of Science 32(1) 145. [Google Scholar]
  12. Kamali R and Binesh AR 2013 A comparison of neural networks and adaptive neuro-fuzzy inference systems for the prediction of water diffusion through carbon nanotubes. Microfluidics and nanofluidics 14(3-4) 575. [Google Scholar]
  13. Azeez D., Ali MAM, Gan KB and Saiboon I 2013 Comparison of adaptive neuro-fuzzy inference system and artificial neutral networks model to categorize patients in the emergency department SpringerPlus 2(1) 416. [Google Scholar]
  14. Chandaran UD, Halim ZA and Sian LK 2012. Study on sulfate reducing bacteria detection using Adaptive Neuro-fuzzy Inference System In 2012 IEEE International Conference on Circuits and Systems (ICCAS) 59. [CrossRef] [Google Scholar]
  15. World Health Organization 1993 Guidelines for drinking-water quality World Health Organization. [Google Scholar]
  16. Math Works: Fuzzy Inference System Modeling – MATLAB & Simulink – MathWorks India, available at, last access: 14 October 2019. [Google Scholar]

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