Combination Forecasting Model of R&D Intensity in Anhui Province Based on IGOWA Operator
DOI:
https://doi.org/10.54097/fcis.v3i1.6351Keywords:
R&D intensity, IGOWA operator, Combination forecasting, Sum of squares of errors, Technological innovationAbstract
Taking the R&D intensity data of Anhui Province from 2006 to 2020 as the sample, the grey prediction model, ARIMA model and Holt Winters non seasonal model were selected to fit and predict the R&D intensity of Anhui Province, and then the IGOWA operator variable weight coefficient combination prediction model based on the minimum criterion of the sum of squares of errors was constructed, and the combination prediction model corresponding to four special values of the operator parameters was taken, Establish an error evaluation index system to illustrate the effectiveness of the model, and analyze the sensitivity of the parameters. Through model evaluation, it can be found that the prediction effect of the combined prediction model in the sample period is significantly better than the three single prediction models, greatly improving the prediction accuracy. Finally, the combined forecasting model is used to predict the R&D intensity of Anhui Province from 2021-2025. The prediction results show that in 2021-2025, the R&D intensity of Anhui Province will continue to rise, and the growth rate is increasing year by year. The scientific research and innovation ability will continue to develop steadily.
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