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Classifying Sonar Signals Using an Incremental Data Stream Mining Methodology with Conflict Analysis
Fong, Simon1; Deb, Suash2; Thampi, Sabu3
2014
Conference NameInternational Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2014
Source PublicationAdvances in Intelligent Systems and Computing
Volume264
Pages171-182
Conference DateMAR 13-15, 2014
Conference PlaceTrivandrum, India
Author of SourceSpringer Verlag
PublisherSPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Abstract

Sonar signals recognition is an important task in detecting the presence of some significant objects under the sea. In military sonar signals are used in lieu of visuals to navigate underwater and/or locating enemy submarines in proximity. Specifically, classification in data mining is useful in sonar signal recognition in distinguishing the type of surface from which the sonar waves are bounced. Classification algorithms in traditional data mining approach offer fair accuracy by training a classification model with the full dataset, in batches. It is well known that sonar signals are continuous and they are collected in streaming manner. Although the earlier classification algorithms are effective for traditional batch training, it may not be practical for incremental classifier learning. Because sonar signal data streams can amount to infinity, the data pre-processing time must be kept to a minimum to fulfill the need for high speed. This paper introduces an alternative data mining strategy suitable for the progressive purging of noisy data via fast conflict analysis from the training dataset without the need to learn from the whole dataset at one time. Simulation experiments are conducted and superior results are observed in supporting the efficacy of the methodology. 

DOIhttps://doi.org/10.1007/978-3-319-04960-1_15
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000391155100015
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Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.University of Macau, Taipa, Macau SAR, China;
2.Cambridge Institute of Technology, Ranchi, India;
3.Indian Institute of Information Technology and Management, Kerala, India
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Fong, Simon,Deb, Suash,Thampi, Sabu. Classifying Sonar Signals Using an Incremental Data Stream Mining Methodology with Conflict Analysis[C]//Springer Verlag:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY,2014:171-182.
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