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Data Mining Approach tool in Fishing Control Activity
IMAM 2017
Year (definitive publication)
2017
Language
English
Country
Portugal
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Abstract
In this research work is described about an implemented process to control the fish type and
weight in order to achieve the identification of non-compliant data reports. Such process is based in a mining model using Artificial Intelligence (AI) settings, namely based on data mining approaches of Naïve Bayes and Decision Trees. We identify fishing patterns based on past data, crossing Vessel Monitor System (VMS) data, with fishing reports (DPE), created by vessel master. Thus, it allows to identify possible non-conforming fishing report based on deviations from the patterns derived from the training mining model. We use real data
from Portuguese fishing activities.
Acknowledgements
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Keywords
data mining AI patterns detection
Fields of Science and Technology Classification
- Civil Engineering - Engineering and Technology
- Environmental Engineering - Engineering and Technology
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