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Reseach Article

Developing an Expert System for Water Types Identification in the Context of Physicochemical Indicators in Aridity-based Regions

by Shah Murtaza Rashid Al Masud
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 11
Year of Publication: 2013
Authors: Shah Murtaza Rashid Al Masud
10.5120/12010-8142

Shah Murtaza Rashid Al Masud . Developing an Expert System for Water Types Identification in the Context of Physicochemical Indicators in Aridity-based Regions. International Journal of Computer Applications. 70, 11 ( May 2013), 43-50. DOI=10.5120/12010-8142

@article{ 10.5120/12010-8142,
author = { Shah Murtaza Rashid Al Masud },
title = { Developing an Expert System for Water Types Identification in the Context of Physicochemical Indicators in Aridity-based Regions },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 11 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 43-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number11/12010-8142/ },
doi = { 10.5120/12010-8142 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:32:38.005130+05:30
%A Shah Murtaza Rashid Al Masud
%T Developing an Expert System for Water Types Identification in the Context of Physicochemical Indicators in Aridity-based Regions
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 11
%P 43-50
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Expert System (ES) is an Artificial Intelligent (AI) technique and program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solutions. The proposed ES presented in this paper is able to easily identify the major water quality types and make appropriate recommendations according to the users' needs. Although water is important for all living substances human-animals-fish-plants-agriculture, but water is continuously contaminated naturally and artificially which ultimately affects on its quality. Due to the lack of knowledge about the quality of water, the harmful effects of water to the animals' body including human, and also necessity of ideal water for agriculture remain unknown. To identify the types of water the researchers had to analyze the physicochemical (physical + chemical) indicators of water such as, positive hydrogen-pH, total dissolved solids-TDS, electrical conductivity-EC, and temperature-T0c. The motivation behind this work was due to the insufficient knowledge about the quality of water and the need to provide novel approaches towards water quality identification and management. A rule-based, web enabled expert system shell: expertise2go was used to design about 56 rules which involved a knowledge component, decision component, design component, graphical user interface component, and the user component.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Expert System Artificial Intelligence Water Types Rule-based Knowledge