Empirical Analysis Of The Aquatic Products Based On Gray System Model

Chinese aquatic products is an important part of national economy, is also an important link related to people’s livelihood. Chinese aquatic products always increase with a stable and rapid speed, so the empirical analysis to this data has its significance. Chinese aquatic products has the feature of exponentially increase, stage, random etc. Because of the influence from politics, economic, environment and nature etc, it appears ambiguity and mic-shocks’ feature. So it’s feasible to analyses this kind data with the time series modeling’s method. With time going by, it appears tendency and random. That fit gray system model’s feature comparatively. So this paper select gray system model to carry out the empirical analysis at last.In the process of research, it firstly carry out empirical analysis to Chinese aquatic products with traditional GM(1,1)model, and using different order’s high order gray system model compare it. We see and analyses the results of different order’s model at last. From thinking of computing accuracy and computing cost, it select GM(2,1) and GM(3,1) to carry out the empirical analysis to Chinese aquatic products. It says, high order gray system model GM(2,1) could get a higher accuracy than traditional model. But the result of high order gray system model GM(3,1) has a big gap, so it couldn’t be used for forecasting. In following part, for keeping the potential relation, Chinese aquatic products is separated into 2 groups with gray correlation analysis. This data included Chinese aquatic products are the output of marine capture, the output of pelagic fishery, the output of mariculture, the output of freshwater capture and the output of freshwater mariculture. Modeling analysis to Chinese aquatic products is carried out with multi-variable gray system model. The result of error computation shows the validity of the model.From above empirical analysis to know, the analyses method that high order gray system model and multi-variable gray system model included the gray system theory to Chinese aquatic products could get a good result. Secondly, the method that using high order gray system model to analyses the time series with the factor of exponentially increase and randomness could be spread, and the method that using multi-variable gray system model to model several correlation data could be spread. Thirdly, the thinking that from seeking single data’s accuracy to using several related data for modeling in today’s big data background, has its significance.It provide the base of data analyses for related departments to make decision and analysis about production and supply, cost and wants, import and export, market circulation, price etc. It might suggest lessons for the future.