Comparison of variable learning rate and Levenberg-Marquardt back-propagation training algorithms for detecting attacks in Intrusion Detection Systems
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 11
Abstract
This paper investigates the use of variable learning rate back-propagation algorithm and Levenberg-Marquardt back-propagation algorithm in Intrusion detection system for detecting attacks. In the present study, these 2 neural network (NN) algorithms are compared according to their speed, accuracy and, performance using mean squared error (MSE) (Closer the value of MSE to 0, higher will be the performance). Based on the study and test results, the Levenberg-Marquardt algorithm has been found to be faster and having more accuracy and performance than variable learning rate backpropagation algorithm.
Authors and Affiliations
Tummala Pradeep , P. Srinivasu , P. S. Avadhani , Y. V. S. Murthy
Keywords
Related Articles
- EP ID EP103028
- DOI -
- Views 101
- Downloads 0
Comparison of Optimal Homotopy Asymptotic Method with Homotopy Perturbation Method of Twelfth Order Boundary Value Problems
In this work, we consider special problem consisting of twelfth order two-point boundary value by using the Optimal Homotopy Asymptotic Method and Homotopy Perturbation Method. Now, we discuss the comparison in between O...
Assessment of Fraud Pretentious Business Region Research Articles Using Data Mining Approaches
In any organization, fraud detection and prevention is daunting task because millions of dollars lost with the different nature of fraudulent activities. Organizations got to engage intelligent and innovative techniques...
Impulse Noise removal in Digital Images
In this paper, we introduce a new class of filter, the modified spatial median filter (MSMF) for the removal of impulse noise in digital images. The proposed filter is compared with four different filtering algorithms ba...
An Efficient Clustering Technique for Message Passing Between Data Points using Affinity Propagation
A wide range of clustering algorithms is available in literature and still an open area for researcher’s k-means algorithm is one of the basic and most simple partitioning clustering technique is given by Macqueen in 196...
Method for forecasting the volume of applications using probabilistic classifier based on Bayesian theorem for recruitment in the government organizations
In this paper, we propose a practical method to estimate or forecast the volume of applications based on Bayesian classifier which is a probability method that makes optimal decision based on known probability distributi...