Application of time series analysis model on stock prediction of small yellow croaker (<i>Larimichthys polyactis</i>) in the southern Yellow Sea

Song Dade; Wang Jintao; Chen Xinjun; Zhong Xiaming; Xiong Ying; Tang Jianhua; Wu Lei

doi:10.3969/j.issn.0253-4193.2020.12.003

Volume 42 Issue 12

Jan. 2021

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Song Dade，Wang Jintao，Chen Xinjun, et al. Application of time series analysis model on stock prediction of small yellow croaker ( Larimichthys polyactis) in the southern Yellow Sea[J]. Haiyang Xuebao，2020, 42(12)：26–33 doi: 10.3969/j.issn.0253-4193.2020.12.003

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Song Dade，Wang Jintao，Chen Xinjun, et al. Application of time series analysis model on stock prediction of small yellow croaker ( Larimichthys polyactis ) in the southern Yellow Sea[J]. Haiyang Xuebao，2020, 42(12)：26–33 doi: 10.3969/j.issn.0253-4193.2020.12.003

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Application of time series analysis model on stock prediction of small yellow croaker (Larimichthys polyactis) in the southern Yellow Sea

doi: 10.3969/j.issn.0253-4193.2020.12.003

1.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
2.
Jiangsu Marine Fisheries Research Institute, Nantong 226007, China

Received Date: 2020-03-25
Rev Recd Date: 2020-07-01

Available Online: 2021-01-06

Publish Date: 2020-12-25

Abstract

Abstract

In this paper, the time series analysis model ARIMA (1, 2, 0) was applied to simulate and predict the stock of small yellow croaker (Larimichthys polyactis) based on the monitoring catches data of canvas stow net in the southern Yellow Sea from 2003 to 2014 and verified by the monitoring catches data of 2015 and 2016. The results showed that the simulated and actual values for the catch yield from 2003 to 2014 were correlated significantly (p<0.05) and the correlation coefficient was 0.881. The relative error between predicted and actual value in 2015 and 2016 were respectively 6.73% and 22.75%, the overall relative error was 14.74% and the regression equation fitted the real situation better, which illustrated that the time series analysis model ARIMA (1, 2, 0) can be applied to simulate the catches trend of L. polyactis and predict the catch stock, especially superior in short-term forecasting. However, in any case the fixed model of L. polyactis is not always suitable for all data analysis, and the values of p, d and q in ARIMA model are considered to be variable according to different time series. Therefore, the optimal values of p, d and q should be determined based on the guidance and analysis of relevant theories in order to avoid copying directly the fixed model.
- small yellow croaker,
- stock,
- time series analysis,
- ARIMA model,
- the southern Yellow Sea

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References

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