East Pacific Ocean squid fishery prediction precision improvement method based on middle-level hydrological characteristics and ship position states

Abstract

The invention discloses an East Pacific Ocean squid fishery prediction precision improving method based on middle-layer hydrological characteristics and ship position states, and the method employs middle-layer water temperature and isotherm dense area positions, ocean current vortexes, cold and warm vortexes and ship position state characteristics to construct precise recognition of a squid fishery in a multiple manner. According to the method, the central fishery is indicated through real-time and predicted hydrology and ship position data, the fishery prediction precision is improved, the East Pacific Ocean fishery is indicated through middle-level hydrology elements, the accuracy is higher, the environmental characteristics of the actual inhabiting water layer of squids are difficult to reflect, and the prediction accuracy is improved. Therefore, the middle-layer hydrological characteristics can reflect the environmental characteristic field of the squid fishery more accurately; real-time ship position and ship position state analysis is adopted to timely grasp the position of the high-yield area of the fishery, the fishery forecasting accuracy is further improved, the purpose of improving the forecasting precision is achieved, and the forecasting precision is expected to be improved by 10-20%; the method effectively solves the difficulty that the squid center fishery is difficult to predict, and provides accurate theoretical guidance for fishery production and fishery transfer.

Description

technical field [0001] The invention belongs to the technical field of marine fishery fishery prediction, and in particular relates to a method for improving the prediction accuracy of East Pacific squid fishery based on mid-level hydrological characteristics and ship position status. Background technique [0002] With the advent of the era of remote sensing, ocean model, ship position monitoring and big data, the prediction of pelagic fisheries and fisheries has become more refined and precise, and it is even more necessary to rely on the three-dimensional spatial detection of the ocean and the description of the fine-scale marine environment, combined with the law of changes in fishing grounds , establish a refined fishery prediction method, and at the same time, with the help of real-time ship position and visualized fishery system software, realize the central fishery prediction based on the predicted hydrological environment and the dynamics of the fishery fleet. In this...

AI Technical Summary

Problems solved by technology

Due to the large changes in the fishery and the difficulty of real-time visualization and availability of the key reference indicators availa

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