Genetic Algorithm to Solve the Markova Forecast Model of the Structure of Agricultural Production Value in Heilongjiang Province

摘要

The structure of agricultural production value of forestry, animal husbandry, fishery industries in Heilongjiang province were studied using Markova forecast model, and the improved genetic algorithm was used to solve Markova forecast model to determine the state transition matrix, and the structure of agricultural production value in Heilongjiang province in 2011 and 2012 was forecasted, providing the reference for optimizing industry structure in Heilongjiang province. The results showed that this method had higher forecast accuracy and it was a short-term prediction method.