NDLI: Evaluation of the performances of ANN and SVM techniques used in water quality classification

Content Provider	IEEE Xplore Digital Library
Author	Bouamar, M. Ladjal, M.
Copyright Year	2007
Description	Author affiliation: Univ. of M'sila, Msila (Bouamar, M.; Ladjal, M.)
Abstract	The modern techniques in control and monitoring of drinking water, acquires a particular attention in the last few years. We attend more and more rigorous follow-ups of the quality of this resource, in order to master an effective control of the risks incurred for the public health. Several methods of control were implemented to meet this aim. In this paper, we present a comparative study of two techniques resulting from the field of the artificial intelligence namely: artificial neural networks (ANN), and support vector machines (SVM). Developed from the statistical learning theory, these methods display optimal training performances and generalization in many fields of application, among others the field of pattern recognition. Applied as classification tools, these techniques should ensure within a multi-sensor monitoring system, a direct and quasi permanent control of water quality. In order to evaluate their performances, a simulation corresponding to the recognition rate, the training time, and the robustness, is carried out. To validate their functionalities, an application of control of drinking water quality is presented.
Starting Page	1047
Ending Page	1050
File Size	250952
Page Count	4
File Format	PDF
ISBN	9781424413775
DOI	10.1109/ICECS.2007.4511173
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-11
Publisher Place	Morocco
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Support vector machines Support vector machine classification Artificial neural networks Water resources Monitoring Public healthcare Artificial intelligence Statistical learning Displays
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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