Abstract
In order to improve the effectiveness of analysis on human capital of migrant worker, a kind of analysis method on human capital of migrant worker based on the gray-level cubic exponential prediction preprocessed by data assimilation is proposed. Firstly, by analyzing the action mechanism of human capital of migrant workers to economic growth, a kind of analysis model on human capital of migrant workers with opening degree and government intervention is designed; secondly, in order to enhance the performance of Kalman filtering algorithm, combining with output features predicted in the model for human capital of migrant workers, the Kalman data assimilation algorithm with local set transformation is designed. And then, the way of division point is set to build the sliding window, and the cubic exponential smoothing algorithm is combined to make real-time segmentation for the data in grey model, so as to acquire the real-time statistic feature of data. Finally, by empirical analysis on human capital of Chinese migrant workers, the algorithm effectiveness is verified.
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Acknowledgements
The research is supported by National Natural Science Foundation of China (71273179, 71303161, 71203146, 71273177, 71573179), Liaoning University Innovation Team Support Program (WT2015009), Social Science Foundation of Liaoning Province (L16BGL038), Youth Project of the Philosophy and Social Science Research, Ministry of Education (13YJC790057), Program for Liaoning Excellent Talents in University (WJQ2015026), Liaoning special Professor support program (2013).
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Tian, Z., Zhang, G., Jiang, J. et al. Grey three index prediction method based on data assimilation preprocessing. Cluster Comput 22 (Suppl 2), 4859–4867 (2019). https://doi.org/10.1007/s10586-018-2407-5
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DOI: https://doi.org/10.1007/s10586-018-2407-5