Predicting System of Flying Squid in North Pacific Based on the Bayesian Theory

Abstract:

Based on the yearly catch data (1994~2011) of Chinese fishery and inversed SST from satellite remote sensing in North Pacific Ocean, we developed the predicting system of fishing grounds using Bayesian probability theory. The system used the client/service mode; while the database used the SQL Server 2000 data management system combining with the Control type GIS technology. The precision verification using historical catch data was conducted and the results showed that the prediction accuracy of fishing and non-fishing ground were 69.46% and 57.15%, respectively, and the total average predict rate of accuracy was 63.31%. The predicting system showed important advising significance in foresting fishing ground and fishing activity of the flying squid in North Pacific Ocean.

• Periodical: Applied Mechanics and Materials (Volumes 336-338)
• Pages: 1968-1973
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.336-338.1968
• Online since: July 2013
• Authors: Feng Hua Tang, Sheng Mao Zhang, Sheng Long Yang, Xue Shen Cui
• Keywords: Bayesian Probability, Flying Squid in North Pacific, Forecast of Fishing Condition, Predicting System

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