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Short-term prediction of marine sensor data with fuzzy clustering


O'Mara, A and Shahriar, MS, Short-term prediction of marine sensor data with fuzzy clustering, International Journal of Pattern Recognition and Artificial Intelligence, 29, (3) Article 1550015. ISSN 0218-0014 (2015) [Refereed Article]

Copyright Statement

Copyright 2015 World Scientific Publishing Company

DOI: doi:10.1142/S0218001415500159


In predicting water quality variables in the short term, a novel technique using fuzzy pattern similarity-based fuzzy clustering has been proposed. The experimental results show that the proposed method outperforms than existing similar methods for sea water temperature and conductivity data sets from a marine sensor network for environmental monitoring. The short-term prediction of water quality variables has immense benefit in aquaculture and fisheries industries for decision-making purposes.

Item Details

Item Type:Refereed Article
Keywords:pattern recognition, fuzzy clustering, prediction, marine sensor data
Research Division:Mathematical Sciences
Research Group:Applied mathematics
Research Field:Biological mathematics
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the mathematical sciences
UTAS Author:O'Mara, A (Mr Aidan O'Mara)
ID Code:106823
Year Published:2015
Deposited By:Information and Communication Technology
Deposited On:2016-02-23
Last Modified:2017-11-01

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