Markov Chain model for the structure of the traditional publishing industry in China

Eryan Zhang Eryan Zhang,Xiaofeng Zhu Xiaofeng Zhu

doi:10.1109/nces.2012.6543659

Eryan Zhang Eryan Zhang, Xiaofeng Zhu Xiaofeng Zhu

https://doi.org/10.1109/nces.2012.6543659

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In order to analyze the structural change of the traditional publishing industry in China, the prediction technique of Markov Chain is applied to conduct research on the prediction problem of the structure of the traditional publishing industry China, and the estimation model of Markov matrix of state transition probability is provided as well. The conclusion shows that the prediction accuracy of the prediction technique is quite high after the error of simulated result has been tested. The prediction technique is applied to forecast the structure of the traditional publishing industry in China from 2012 to 2016. The application of Markov Chain prediction model in forecasting the structural change trend of the traditional publishing industry in China has greatly expanded the fields where the prediction technique of Markov Chain can be put into practice, and the data about the structural transition of the traditional publishing industry in China can hopefully offer a new perspective on looking into and solving issues to ensure the healthy and sound development of China's changing publishing industry.

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