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Short-term prediction of marine sensor data with fuzzy clustering
Citation
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
Abstract
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 |
| Downloads: | 0 |
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