DocumentCode
1875634
Title
The Application of Neural Networks and Rough Set in Creativity Measurement
Author
Yu, Jiayuan
Author_Institution
Dept. of Psychol., Nanjing Normal Univ., Nanjing, China
fYear
2010
fDate
10-12 Dec. 2010
Firstpage
1
Lastpage
3
Abstract
Williams Creativity Test B (WCTB) and Adolescent Scientific Creativity Scale (ASCS) were used to measure the creative affective and scientific creativity for 550 middle school students. Generalized regression neural network (GRNN) and multivariable linear regression (MLR) were used for modeling and testing. The result showed the fitting error of GRNN model was lower than the error of MLR. In the rough set analysis, the data was discretized with SOM network. After attribute reduction, eight rules were extracted.
Keywords
neural nets; rough set theory; Williams creativity test B; adolescent scientific creativity scale; creativity measurement; generalized regression neural network; multivariable linear regression; neural networks; rough set; Artificial neural networks; Complexity theory; Data models; Linear regression; Mathematical model; Psychology; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5391-7
Electronic_ISBN
978-1-4244-5392-4
Type
conf
DOI
10.1109/CISE.2010.5676983
Filename
5676983
Link To Document