Simulation analysis on evaluation model for the rationality of college budget expenditure performance
- DOI
- 10.2991/amcce-15.2015.273How to use a DOI?
- Keywords
- budget expenditure; performance evaluation; neural network;
- Abstract
During rationality evaluation process for college budget expenditure performance, when traditional algorithm is adopted to evaluate, the accuracy and practicability of expenditure cannot be considered at the same time, thus, assessment results have poor accuracy. For this, a rationality evaluation method for college budget expenditure performance based on improved genetic algorithm is put forward. The difficulty of rationality evaluation for the current budget expenditure performance of college is analyzed, to obtain quantified expressions of rationality evaluation factors effecting college budget expenditure performance, quantified results regarded as input, the rationality evaluation results of expenditure performance as output, weights and threshold of neural network are optimized with genetic algorithm, nonlinear relationship of rationality assessment model of neural network is built as well, so as to achieve the establishment of rationality evaluation model of college budget expenditure performance. Simulation results show that the rationality evaluation method of college budget expenditure performance based on improved genetic algorithm, have high accuracy and strong adaptability.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hongwang Li PY - 2015/04 DA - 2015/04 TI - Simulation analysis on evaluation model for the rationality of college budget expenditure performance BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.273 DO - 10.2991/amcce-15.2015.273 ID - Li2015/04 ER -