DocumentCode
502780
Title
Undergraduate practice teaching job quality assessment based on artificial fish-BP neural network
Author
Gao, Yongge ; Zhang, Yanhong ; Li, Lihua
Author_Institution
Hebei Univ. of Eng., Handan, China
Volume
2
fYear
2009
fDate
8-9 Aug. 2009
Firstpage
379
Lastpage
382
Abstract
In order to solve the problems in undergraduate practice teaching job, the evaluation simulation model was set up using artificial fish-swarm-neural network; taking the experimental teaching, practice teaching, graduate design thesis, laboratory management and equipment for the input layer, the undergraduate practice teaching job quality for the output layer, establishing artificial neural network model and training and testing for the network using actual data. Practice shows that the model has better recognition accuracy. Finally, the assessment results digitized came to the conclusion that can be accurately, intuitively reflect the merits of the undergraduate theory teaching job quality, thus demonstrating that the artificial fish-BP neural network has broad prospects the evaluation at the undergraduate practice teaching job quality of colleges and universities.
Keywords
artificial intelligence; backpropagation; engineering education; mobile robots; BP neural network; artificial fish; artificial neural network model; evaluation simulation model; swarm-neural network; undergraduate practice teaching job quality assessment; Artificial neural networks; Education; Educational institutions; Engineering management; Laboratories; Management training; Marine animals; Neurons; Quality assessment; Quality management; artificial fish-BP neural network; job quality assessment component; undergraduate prctice teaching;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location
Sanya
Print_ISBN
978-1-4244-4247-8
Type
conf
DOI
10.1109/CCCM.2009.5267921
Filename
5267921
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