Flock 1 Data Multi-objective Evolutionary Algorithm for Turbulent Flow Detection
نویسنده
چکیده
ABSTRACT: This study has demonstrated a design tool for turbulent flow detection in Flock 1 data using Multi-Objective Evolutionary Algorithm which based on Pareto optimal solutions. The Flock 1 data along the Suez Canal, Egypt and Farasan Islands, Saudi Arabia are involved in this study. The study also shows that Multi-Objective Evolutionary Algorithm provides an accurate pattern of turbulent water flow in both Flock 1 data. This shown by 70% for water turbulent flow is associated with look-alikes, and 25% for coral and 5 % for land/sediment using the receiver –operational characteristics (ROC) curve. The MOGA also shows excellent performance in Flock 1 data. In conclusion, Multi-Objective Evolutionary Algorithm can be used as an automatic detection tool for ocean turbulent flow in Flock 1 data.
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