Optimal brain surgeon pruning of neural network models of manufacturing processes
Joint Authors
Kazim, Baha Ibrahim
Mutlak, Ali Khudayr
Source
Issue
Vol. 11, Issue 3 (30 Sep. 2005), pp.495-508, 14 p.
Publisher
University of Baghdad College of Engineering
Publication Date
2005-09-30
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Abstract EN
In this paper ,Optimal Brain Surgeon (OBS) pruning algorithm is proposed to optimize network architecture with respect to testing patterns error and overcoming the over fitting problem .
Turning process is used as case study to improve the performance of the neural network – surface roughness model .Using the proposed algorithm reduced the prediction error on testing patterns from 0.6237 to 0.2854 based on the absolute percent error estimate .Also.
noticeable improvement is made in correlation coefficient from 0.8656 to 0.9807 making the network more reliable for new operating conditions.
American Psychological Association (APA)
Kazim, Baha Ibrahim& Mutlak, Ali Khudayr. 2005. Optimal brain surgeon pruning of neural network models of manufacturing processes. Journal of Engineering،Vol. 11, no. 3, pp.495-508.
https://search.emarefa.net/detail/BIM-360752
Modern Language Association (MLA)
Kazim, Baha Ibrahim& Mutlak, Ali Khudayr. Optimal brain surgeon pruning of neural network models of manufacturing processes. Journal of Engineering Vol. 11, no. 3 (Sep. 2005), pp.495-508.
https://search.emarefa.net/detail/BIM-360752
American Medical Association (AMA)
Kazim, Baha Ibrahim& Mutlak, Ali Khudayr. Optimal brain surgeon pruning of neural network models of manufacturing processes. Journal of Engineering. 2005. Vol. 11, no. 3, pp.495-508.
https://search.emarefa.net/detail/BIM-360752
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 508
Record ID
BIM-360752