BP Neural Network-Based Research of University Science Research Capability Evaluation

Author

Liu, Weiwei ; Shi, Chunsheng

Author_Institution

Sch. of Manage., Harbin Inst. of Technol., Harbin

Volume

1

fYear

2009

fDate

7-8 March 2009

Firstpage

543

Lastpage

546

Abstract

Based on the substance of university science research capability (USRC) and the highly self-organized, self-adapted and self-learned characteristics of back propagation (BP) neural network, the paper conducts a research on evaluation of USRC, in which an evaluation index system of USRC is constructed and a 15-7-1-typed BP neural network with three layers is presented to evaluate USRC, which provides a BP neural network-based methodology for evaluation of USRC with multiple inputs.

Keywords

backpropagation; educational computing; educational institutions; 15-7-1-typed backpropagation neural network; evaluation index system; selfadapted characteristics; selflearned characteristics; selforganized characteristics; university science research capability evaluation; Biological neural networks; Computer science education; Data envelopment analysis; Educational technology; Neural networks; Paper technology; Production systems; Project management; Quality management; Technology management; BP Neural Network; Capability Evaluation; Science Research;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-1-4244-3581-4

Type

conf

DOI

10.1109/ETCS.2009.129

Filename

4958832