Abstract
Marine life has significant impact on our planet, providing food, oxygen and biodiversity. But, 90 percent of the large fish are gone primarily because of overfishing, according to the 2010 Census of Marine Life. Thus it is desirable to detect fishing activities in the ocean. Satellite AIS (Automatic Identification System) is a vessel identification system that monitors the position of ships worldwide for collision avoidance, allowing us to track vessels on the ocean. AIS equipment is required to be fitted aboard international voyaging ships that are 300 tons or above, and all passenger ships.
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Notes
- 1.
The null hypothesis for paired samples t-test is that the mean difference between paired observations is zero. On significance level 0.05, the difference is statistically significant when p-value is less than 0.05.
- 2.
The null hypothesis for Shapiro-Wilk test is that the population is normally distributed. On significance level 0.05, if the p-value is greater than 0.05, the null hypothesis that the data came from a normally distributed population cannot be rejected.
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de Souza, E.N., Kristina Boerder, B.W., Matwin, S.: Improving fishing pattern detection from AIS using data mining and machine learning (to appear)
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Jiang, X., Silver, D.L., Hu, B., de Souza, E.N., Matwin, S. (2016). Fishing Activity Detection from AIS Data Using Autoencoders. In: Khoury, R., Drummond, C. (eds) Advances in Artificial Intelligence. Canadian AI 2016. Lecture Notes in Computer Science(), vol 9673. Springer, Cham. https://doi.org/10.1007/978-3-319-34111-8_4
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DOI: https://doi.org/10.1007/978-3-319-34111-8_4
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