Season tendency superposing—Markov forecasting model and its application
A new forecasting model combined the season tendency superposing and Markov forecasting methods together is presented to forecast the average yield of rapeseed. It has the merits of both simplicity of calculation and high forecasting precision to forecast data sequences with season tendency superpos...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2008-05-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/j.issn.1008-9209.2008.03.012 |
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| Summary: | A new forecasting model combined the season tendency superposing and Markov forecasting methods together is presented to forecast the average yield of rapeseed. It has the merits of both simplicity of calculation and high forecasting precision to forecast data sequences with season tendency superposing and heavy random fluctuation. The forecasting model was based on historical data of the average yield of the rapeseed from 1949 to 1996 in Zhuji, Zhejiang, and forecast the average yield of the rapeseed from 1997 to 2003 in Zhuji, Zhejiang by the season tendency superposing—Markov forecasting model. The forecasting precision of season tendency superposing—Markov forecasting model from 1997 to 2003 was 97.9%, 97.9%, 97.9%, 97.9%, 98.8%, 97.7%, 98.4% respectively, and in the season tendency superposing model, it was 76.1%, 68.9%, 70.9%, 97.9%, 82.5%, 76.9%, 82.2% respectively. It shows that the season tendency superposing—Markov forecasting model can improve the forecasting precision highly when forecasting the data sequences wih season tendency superposing and heavy random fluctuation. |
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| ISSN: | 1008-9209 2097-5155 |