Study on Grey-Markov method and its application in agricultural production forecast

Grey-Markov forecasting model has the merits of both GM (1, 1) forecast and Markov transition probability matrix forecast, which integrates the grey system and the Markov theory into a higher precision model. Its agricultural application of primary product yield forecast was addressed in this paper. The data of oil plant and cotton yield from 1977 to 2005 in China was used as two forecasted examples, providing references for agricultural production forecast application. Meanwhile, compared with GM (1, 1) forecast model, the result showed that Grey-Markov forecasting model was more suitable for heavy random fluctuation and the forecast precision was satisfactory.