Research on Performance Evaluation Method of Emergency Communication Network in the Background of BP Neural Network

2020 ◽  
Vol 09 (05) ◽  
pp. 668-673
Author(s):  
小勇 丁
2021 ◽  
Vol 251 ◽  
pp. 02097
Author(s):  
Mingle Zhou ◽  
Shengli Cao ◽  
Ran Wang ◽  
Yu Wang

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.


2013 ◽  
Vol 734-737 ◽  
pp. 2925-2929
Author(s):  
Ye Jiao Liu ◽  
Zhi Chao Tian ◽  
Dong Mei Huang

The index system of coalmine safety management performance evaluation is established, the structure and principle of evaluation method of BP neural network is introduced and the model of performance evaluation based on BP neural network is constructed, in which the input and output parameters as well as the connection weights and domain values of every layer are defined; and based on the matlab6.0 software, it uses internal tool boxes of neural network and sample data to train the neural network that has been constructed and forecast the coalmine safety management performance.


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