Title :
Employee demission risk assessment based on AHP and BP neural network
Author_Institution :
Coll. of Economic & Manage., Heilongjiang August First Land Reclamation Univ., DaQing, China
Abstract :
Employee demission risk management is an indispensable component to the human resource department of one enterprise. Employee demission risk mainly reflects the demission warning of employees and the management level of employers, to some extent, reducing the risk and loss stemming from employee demission and, hence, the main focus of the paper is to design a risk identification and assessment system. By the combination of AHP and BP neural network, the paper constructs the risk assessment model of employee demission risk, and applies a BP neural network for training and testing samples that stems from AHP. The research result indicates that the risk assessment model based on AHP and BP neural network is not only applicable, but also it can reduce the influence of subjectivity.
Keywords :
backpropagation; neural nets; personnel; recruitment; risk management; termination of employment; AHP; BP neural network; analytic hierarchy process; employee demission risk assessment; human resource department; risk identification; risk management; Environmental economics; Humans; Intelligent networks; Intelligent systems; Level control; Monitoring; Neural networks; Psychology; Risk analysis; Risk management;
Conference_Titel :
Grey Systems and Intelligent Services, 2009. GSIS 2009. IEEE International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4914-9
Electronic_ISBN :
978-1-4244-4916-3
DOI :
10.1109/GSIS.2009.5408153