DocumentCode
2649706
Title
Software component retrieval method based on PSO-RBF neural network
Author
Su-Wei, Guo
Author_Institution
Coll. of Inf. Sci. & Technol., Beijing Univ. of Chem. Technol., Beijing, China
Volume
7
fYear
2010
fDate
16-18 April 2010
Abstract
Software component retrieval is the core part in software development methodology based on component. In the paper, particle swarm optimization algorithm and RBF neural network is presented to software component retrieval. Radial basis function neural network which is simplified as RBFNN is a kind of feed forward neural network, which encounters the local optimization problems. particle swarm optimization algorithm is applied to select appropriate parameters in the radial basis function neural network. The case data are applied to prove the performance of the method proposed in the paper. By the experimental analysis, the software component retrieval model based on PSO-RBF neural network is feasible and effective.
Keywords
object-oriented programming; particle swarm optimisation; radial basis function networks; software engineering; feed forward neural network; local optimization problems; particle swarm optimization algorithm; radial basis function neural network; software component retrieval method; software development methodology; Computer networks; Educational institutions; Feedforward neural networks; Feeds; Information retrieval; Neural networks; Particle swarm optimization; Programming; Radial basis function networks; Software algorithms; neural network; particle swarm optimization; retrieval; software component;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5485451
Filename
5485451
Link To Document