Government Performance Assessment Based on BP Neural Network

Abstract:

Improvement of government performance is always the fundamental goals and the fundamental value that the public administration pursues. Proceed from the special duality identity of government, this paper designs an index system on government performance. And then predicts the quantitative assessment of government performance based on BP neural network in order to build a forward-looking quantitative assessment system. The accuracy and effectiveness of the system is verified by experiments.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 1141-1146
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.1141
• Online since: July 2012
• Authors: Hai Ping Liu, Zhi Jun Chen
• Keywords: BP Neural Network (BPNN), Government, Performance Assessment

References

[1] Wang Zhengqun, Chen Shifu, Chen Zhaoqian, A parallel learning approach for neural network ensemble, Chinese journal of computers, 2005, vol: 28, iss: 3, pp: 402 -408.

[2] Wang Zhengqun, Chen Shifu, Chen Zhaoqian, An active learning approach for neural network ensemble, Journal of computers research and development, 2005, vol: 42, iss: 3, pp: 375 -380.

[3] Mark G. Popovich, Create high-performance government organizations, Beijing: China renmin university press, (2002).

[4] Song Yibin, Wang Peijin, An improved BP algorithm for FNN and its application, Computer engineering, 2003, vol: 29, iss: 14, pp: 109 -111.

[5] Wang Jianjun, Xu Zongben, Approximation method of multivariate polynomials by feedforward neural networks, Chinese journal of computers, 2009, vol: 32, iss: 12, pp: 2482 -2488.