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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE)
Urvashi Rahul Saxena
JSS Academy of Technical Education.Noida(U.P)
Computer Science & IT Education Engineering

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Multi-Party Security System using Artificial Neural Networks Urvashi Rahul Saxena; S.P Singh
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 3: September 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (132.595 KB)

Abstract

Multi-Party Security System is an improvised version of various security systems available using Artificial Neural Networks (ANN’s) as an Intelligent Agent for Intrusion Detection. This Paper focuses how inputs can be preserved to serve as a measure for securing communication protocol between two parties using privacy protocols at the hidden layer of Multi-layer Perceptron model. Various neural network structures are observed for evaluating the optimal network considering the number of hidden layers. Results depict that the generated system is capable of classifying records with about 90% of accuracy when two hidden layers are engulfed and the accuracy reduces to 87% with one hidden layer under observation.DOI: http://dx.doi.org/10.11591/ij-ai.v1i3.739
Integrating Neuro-Fuzzy Systems to Develop Intelligent Planning Systems for Predicting Students’ Performance Urvashi Rahul Saxena
International Journal of Evaluation and Research in Education (IJERE) Vol 1, No 2: December 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (117.919 KB)

Abstract

This paper presents a simulation of Neuro-Fuzzy application for analyzing students’ performance based on their CPA and GPA. This analysis is an attempt for extension of Analysis on Student’s Performance Using Fuzzy Systems. This paper focuses to support the development of Intelligent Planning System (INPLANS) using Fuzzy Systems, Neural Networks, and Genetic Algorithms which will be used by the Academic Advisory Domain in educational institutions by evaluating and predicting students’ performance as well as comparing the results with the previous study. The Neuro-Fuzzy model is feed-forward architecture with five layers of neurons and four connections. System evaluation has been done for about 20- 26 cases of students’ results. The results depict that there has been a significant improvement in the performance of students’ as compared to the prediction of the same case using Fuzzy Systems.DOI: http://dx.doi.org/10.11591/ijere.v1i2.738
Co-Authors S.P Singh