ESTIMATION OF PELAGIC FISH DISTRIBUTION IN INNER BAY WITH MACHINE LEARNING

Abstract

 Pelagic Fishes are the main target species in the inner bay, and the fluctuation of their catches and the formation of fishing grounds associated with natural and anthropogenic environmental changes are of great concern. In this study, we construct a statistical model to estimate the distribution of floating fishes in the inner bay using Gradient Boosting, which is one on the highly efficient machine learning techniques. Then we estimate catch of anchovy(Engraulis japonicus) in Ise Bay and Mikawa Bay. The model reproduced distribution pattern of anchovy well.