DOI: 10.14704/nq.2018.16.5.1350

Civil Servants’ Cognitive Evaluation of Performance Appraisal Based on Computational Neuroscience

Qiuhong Sun, Xinhang Xu, Qiong Han

Abstract


With social development and scientific and technological progress, China is committed to building a service-oriented government, which will put forward higher requirements for the government administration efficiency and levels, and at the same time incorporates civil servants' perceptions of government management into the thinking of transforming administrative methods. Based on computational neuroscience, this paper studies civil servants' cognitive evaluation of performance appraisal, and more realistically simulates the entire evaluation process. The research results show that there are differences in the cognitive evaluation of civil servants at different stages of performance appraisal. At the same time, under the influence of information interference, cognitive evaluation will also show various changes. Based on computational neuroscience, this paper studies the civil servants' cognitive evaluation of performance appraisal, which is beneficial to the orderly development of performance appraisal, and can also promote the transformation of government management concepts and functions.

Keywords


Computational Neuroscience; Civil servant; Performance appraisal; Cognitive evaluation

Full Text:

PDF

References


Hirasawa M, Yamamoto M, Kawano K, Furukawa A. An experiment on extrasensory information transfer with electroencephalogram measurement. Journal of International Society of Life Information Science2017; 14(2): 43-48.

Franco P,Värri A. Experiments of the sonification of the sleep electroencephalogram. Finnish Journal of Ehealth&Ewelfare2015; 7(2-3): 65-74.

Teixeira C, Cardoso A, Gomes MPC, Sales F, Dourado A. An alternative methodology for the estimation of frequency changes in electroencephalogram signals. Experiment@ International Conference2016; 302-305. IEEE.

Tang X, Yu K, Liu W, Gao T, Xu Y, Zeng Y, Peng Y. The set partitioning in hierarchical trees algorithm for data compression in ambulatory electroencephalogram systems. Journal of Medical Imaging & Health Informatics2016; 6(2): 494-98.

Inkaew N, Charoenkitkamjorn N, Yangpaiboon C, Phothisonothai M, Nuthong C. Frequency component analysis of brain evoked potential recording on various visual tasks: Steady-state visual evoked potential experiment. International Conference on Knowledge and Smart Technology2015; 180-83. IEEE.

Hashemi SS, HajiaghaSHR, ZavadskasEK, Mahdiraji HA. Multicriteria group decision making with electre iii method based on interval-valued intuitionistic fuzzy information. Applied Mathematical Modelling2016; 40(2): 1554-64.

Xian S, Dong Y, Yin Y. Interval-valued intuitionistic fuzzy combined weighted averaging operator for group decision making. Journal of the Operational Research Society2017; 68(1): 1-11.


Supporting Agencies





| NeuroScience + QuantumPhysics> NeuroQuantology :: Copyright 2001-2018