Classification of Ammonia in water for Oil and Gas Industry using Case Based Reasoning (CBR)

Muhamad Faruqi, Zahari and M. S., Najib and Kamarul Hawari, Ghazali and Fathimah, Abdul Halim and Abdul Aziz, Mohd Azoddein (2016) Classification of Ammonia in water for Oil and Gas Industry using Case Based Reasoning (CBR). Journal of Electrical, Electronics, Control and Instrumentations Engineering (JEECIE), 1 (7). pp. 34-37. ISSN 2462-2303. (Published)

	PDF Classification of Ammonia in water for Oil and Gas Industry using Case.pdf Restricted to Repository staff only Download (357kB) | Request a copy
Preview	PDF fkee-2016-sharfi-Classification of Ammonia in water for Oil.pdf Download (22kB) | Preview

Abstract

Toxic gasses are exists in environment such as benzene, ammonia and others. Ammonia highly dissolves in water which is sources of human and other species. If the ammonia have high concentration, the effect of human health will be dangerous. Then, using proper monitoring and wastewater management the hazard can be prevented. This paper proposed the intelligence classification technique using an Electronic Nose (E-nose) measurement.The sensor array in the E - nose are used for the inputs of the Case Based Reasoning (CBR) for intelligent classification. The experimental result shows that the technique accomplished to classify with high accuracy which is 100% of accuracy.

Item Type:	Article
Additional Information:	Colloquium on Robotics, Unmanned Systems and Cybernetics 2014 (CRUSC), Universiti Malaysia Pahang, 20 November 2014
Uncontrolled Keywords:	CBR, e-nose, ammonia, classification, water
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TP Chemical technology
Faculty/Division:	Faculty of Chemical & Natural Resources Engineering Faculty of Electrical & Electronic Engineering
Depositing User:	Mr. Mohd Fakhrurrazi Adnan
Date Deposited:	26 Oct 2015 03:34
Last Modified:	22 Jan 2018 03:45
URI:	http://umpir.ump.edu.my/id/eprint/9762
Download Statistic:	View Download Statistics

Actions (login required)

View Item