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Fuzzy Logic Inference Index to Assess the Water Quality of Tigris River within Baghdad City


 
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1. Title Title of document Fuzzy Logic Inference Index to Assess the Water Quality of Tigris River within Baghdad City
 
2. Creator Author's name, affiliation, country Salam Hussein Ewaid; Technical Institute of Shatra, Southern Technical University, Iraq; Iraq
 
2. Creator Author's name, affiliation, country Turki Diwan Hussein; Dept. of Biology, College of Science, University of Baghdad, Iraq; Iraq
 
2. Creator Author's name, affiliation, country Faiza Kadhim Emran; Dept. of Biology, College of Science, University of Baghdad, Iraq; Iraq
 
3. Subject Discipline(s) Biology
 
3. Subject Keyword(s) Water quality index, Iraqi Rivers, Fuzzy logic.
 
4. Description Abstract This study aimed to develop a new water quality index for routine assessment of the river water quality for drinking purpose based on fuzzy logic artificial intelligence method. Four water quality parameters were involved in light of their significance to Iraqi waters, these parameters are biological oxygen demand, and total dissolved solids, total hardness, and fecal coliform. Fuzzy logic inference system with specific rules was developed by Matlab software using Mamdani fuzzy logic Max–Min inference system method. To evaluate the performance of this new fuzzy water quality index (FWQI), tests were conducted using the Iraqi standards for drinking water quality and the 2017 data set of Tigris River within Baghdad. Results revealed the FWQI ability to assess the water quality of Tigris River during the period of the study and that the method of fuzzy inference system was a simple, valuable and applied water quality evaluation tool for human drinking water of Iraqi rivers.
 
5. Publisher Organizing agency, location Mustansiriyah University
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2019-03-10
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://mjs.uomustansiriyah.edu.iq/ojs1/index.php/MJS/article/view/617
 
10. Identifier Digital Object Identifier (DOI) http://dx.doi.org/10.23851/mjs.v29i3.617
 
11. Source Title; vol., no. (year) Al-Mustansiriyah Journal of Science; Vol 29, No 3 (2018): ICSSSA 2018 Conference Issue
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions Copyright (c) 2019 Al-Mustansiriyah Journal of Science
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