Title :
The Application of Neural Networks and Rough Set in Creativity Measurement
Author_Institution :
Dept. of Psychol., Nanjing Normal Univ., Nanjing, China
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;
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
DOI :
10.1109/CISE.2010.5676983
