Abstract
Open government affairs (OGA) play an important role in promoting national governance system and capacity. In order to realize an open and efficient government, it is necessary to scientifically evaluate the performance of government. The effect of OGA can be improved continuously through the feedback from evaluation, which is beneficial for the sustainable development of OGA. However, with the continuous development of OGA, the existing methods of evaluation are faced with such problems as poor-timeliness, high-cost and subjective uncertainty, which are difficult to satisfy the demands of performance evaluation of OGA. Therefore, this paper puts forward a performance evaluation method based on T-S fuzzy neural network. Our method has a strong ability of data processing, which can simplify the work flow. The T-S fuzzy neural network was trained and tested through using the performance evaluation data of all districts and counties in Shandong Province, China. Finally, the evaluation results offered by our method are highly accurate. Hence, our method is suitable for the performance evaluation of OGA, it can continuously enhance the improvement of government’s performance management and capacity building so as to promote the sustainable development of OGA.
Highlights
Government data has its own uniqueness[1]
Compared with the traditional third-party performance evaluation method of Open government affairs (OGA), the evaluation method based on T-S fuzzy neural network has the advantages of high efficiency and accuracy, which can promote the development of OGA effectively
The results show that the government performance evaluation method based on T-S fuzzy neural network has remarkable accuracy
Summary
With the further development of OGA, the data of performance evaluation shows a trend of exponential growth. Both the resources required for the performance evaluation and the difficulty of the work increase sharply. Y In the method of traditional third-party performance evaluation, the accurate ratio index is generally used to reflect the level of OGA. Y The traditional third-party evaluation generally uses linear analysis method to calculate the final results. The fuzzy neural network and the expert experience in third-party performance evaluation are perfectly combined in this model. Compared with the traditional third-party performance evaluation method of OGA, the evaluation method based on T-S fuzzy neural network has the advantages of high efficiency and accuracy, which can promote the development of OGA effectively
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