Oceanographic features selection to predict the tuna potential fishing zones using SFFS method

Abstract

To be able to maintain the tuna fishing activities, many studies are proposed to assist the fishermen to find the tuna potential fishing zones (PFZ). Determining the oceanographic feature of tuna PFZ is one of the main tasks to predict the tuna PFZ. Different kind of tuna dwell in different habitat, that is why in this research, the feature selection for the oceanographic parameters will be conducted each for specific kind of tuna. One of the most promising feature selection methods is the Sequential Forward Floating Selection (SFFS). Our contribution in this paper is to propose a framework of oceanographic feature selection for Albacore tuna PFZ and Bigeye tuna PFZ utilizing the SFFS method. The experimental results have shown that Albacore and Bigeye PFZ are influenced by different oceanographic feature and SFFS yields a good accuracy of PFZ prediction that reaches 88.81%.

Spatial and temporal clustering analysis on chlorophyll-a data distribution

“…As noted previously, the oceanographic parameters that are often used in studies of the determination of potential fishing zones are sea surface temperature and chlorophyll-a. According to the results of such studies, chlorophyll-a is the most influential in determining potential fishing zone [12], [13]. This proves that data on the dis-tribution of chlorophyll-a are needed to determine potential areas of fishing.…”