Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Security risk analysis is the thrust area for the information based world. The researchers in this field deployed numerous techniques to overcome the information security oriented problem. In this paper the researcher tried for a approach of using anomaly detection for the risk reduction. The hub initiative for this work is that the anomalies are the deviation which could increase the percentage of risk. The anomaly detection is guided by the PCA and the genetic based multi class classifier is used. The classification is induced by the decision tree approach were the genetic algorithm is set out for the optimization in the process of finding the nodes of the tree. The proposed approach is evaluated with the bench mark on PCA based ANN classifier. The proposed approach outperforms the existing one. The results are demonstrated.
C.Kavitha. 2014. \u201cOptimized Anomaly based Risk Reduction using PCA based Genetic Classifier\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C7): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Neural Networks and Rules-based Systems used to Find Rational and
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Security risk analysis is the thrust area for the information based world. The researchers in this field deployed numerous techniques to overcome the information security oriented problem. In this paper the researcher tried for a approach of using anomaly detection for the risk reduction. The hub initiative for this work is that the anomalies are the deviation which could increase the percentage of risk. The anomaly detection is guided by the PCA and the genetic based multi class classifier is used. The classification is induced by the decision tree approach were the genetic algorithm is set out for the optimization in the process of finding the nodes of the tree. The proposed approach is evaluated with the bench mark on PCA based ANN classifier. The proposed approach outperforms the existing one. The results are demonstrated.
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