Abstract
Small and medium-sized enterprises are the main part of the regional economy. The development of SMEs aims to stabilize growth, adjust structure, promote reform and enhance the entrepreneurship and innovation. So it’s important to research on the operation situation of SMEs for central and local governments. In recent prediction studies of the operational states of SMEs, we find that there are problems of “multicollinearity” and “over-fitting” in large monitoring index system. In the paper, the genetic algorithm was adopted to reduce the dimension of independent variables. After that, the indexes could be used as independent variables of prediction model. Then the prediction model was constructed by the group-method of data handling which had unique superiority in complex system modeling. Finally, we established GA-GMDH prediction system model. The prediction effect of the operation condition of SMEs in Chengdu showed the system model owned high prediction precision and better effect, effectively reduced the association strength between independent variables.
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Wang, R., Ling, B., Wang, F. (2017). Application of GA-GMDH Prediction Model in Operational Monitoring of SMEs in Chengdu. In: Xu, J., Hajiyev, A., Nickel, S., Gen, M. (eds) Proceedings of the Tenth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-10-1837-4_44
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DOI: https://doi.org/10.1007/978-981-10-1837-4_44
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