Research On China-ASEAN Fishery Production Forecast Based On Grey Theory

China and ASEAN countries have abundant marine fishery resources and great development potential,and have broad prospects for cooperation in marine fisheries.The maritime cooperation between China and ASEAN countries is an important strategic choice for China's development of the marine economy in the new era.The analysis and prediction of the production of ASEAN marine fishery is not only the functional demand of the China-ASEAN marine big data platform fishery,but also the comprehensive understanding of the status of China and ASEAN marine fishery industry,and provide the correct direction and strategic support for China-ASEAN fishery cooperation..The existing research stays in the theoretical stage,and there are few practical applications for predictive analysis of ASEAN fishery production.Therefore,this paper combines the gray system theory to predict the production of ASEAN marine fishery,which has certain theoretical significance and high practical value.This paper selects China and the ASEAN countries in which the two fisheries economies of Myanmar and Malaysia occupy an important position in the national economy.Firstly,it analyzes the background of China-ASEAN fishery economic development and the methods and limitations of current fishery production forecasting.Then,according to the basic economic principles,the relevant indicators affecting fishery production are selected,and the gray correlation analysis method was used to obtain the high correlation index related to fishery production.Based on the traditional GM(1,1)prediction model combined with the actual situation of China-ASEAN fishery production forecasting,an improved RCGM model based on residual correction is proposed for the residual problem;the traditional GM(1,1)model is discrete.To the continuous jump problem,a BDGM model based on discretization improvement is proposed.For the single variable problem,an MVGM model based on multivariate improvement is proposed.In order to solve the problem that the single gray model does not have linear factors and data fluctuations,a grey combination model is proposed,including gray linear regression combined model-GLRM model and grey Verhulst Markov model-GVMM model.The experimental data and these models were used to predict the fishery production in China,Myanmar and Malaysia,and the prediction errors of each model were compared and analyzed based on the prediction results.The experimental results show that the gray combination model is generally excellent under the condition that the data meets the requirements.In GM(1,1)and its improved model,the RCGM model in the improved model of GM(1,1)has better prediction effect,and the effect of MVGM model is greatly affected by the correlation degree of selected indicators.In addition,fishery production in China,Myanmar,and Malaysia in 2019-2028 was predicted using a suitable model.Finally,the research results of this paper are applied to the global fishery database module of China-ASEAN Ocean Big Data Platform.Through this module,we can know the historical data related to fisheries in China and ASEAN countries.We can predict the annual fishery production value of China and ASEAN,and verify the practicality and effectiveness of the China-ASEAN fishery production forecasting model through practical application.Provide better data services and forecasting references for people.