DocumentCode
2262130
Title
An Improved Neural Network Algorithm and Its Application on Enterprise Strategic Management Performance Measurement Based on Kirkpatrick Model
Author
Li, Tielin ; Yang, Yamei ; Liu, Zhibin
Author_Institution
Econ. & Manage. Coll., Shijiazhuang Railway Inst., Shijiazhuang
Volume
1
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
861
Lastpage
865
Abstract
To evaluate the enterprises´ strategic management performance scientifically and accurately, this paper proposes the improved BP neural network model based on Kirkpatrick model which imports the adjustable activation function and the Levenberg-Marquardt optimization algorithm. The improved model not only can simulate the expert in evaluating the strategic performance and avoiding the subjective mistakes in the evaluation process, but also enhance the learning accuracy and the algorithm convergence speed greatly. The strategic management performance evaluation of 14 enterprises in Hebei Province shows that the improved model is stable and reliable, and this method to evaluate the enterprises´ strategic management performance is feasible.
Keywords
backpropagation; neural nets; optimisation; strategic planning; transfer functions; BP neural network algorithm; Kirkpatrick model; Levenberg-Marquardt optimization algorithm; activation function; enterprise strategic management performance measurement; Artificial neural networks; Cities and towns; Educational institutions; Energy management; Mathematical model; Measurement; Neural networks; Neurons; Power generation economics; Technology management; Enterprise Strategic Management; Kirkpatrick Model; Neural Network Algorithm; Performance Measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3497-8
Type
conf
DOI
10.1109/IITA.2008.168
Filename
4739694
Link To Document