Fuzzy Logic, Artificial Neural Network and Genetic Algorithm over Sylvester Law of Inertia based Data Analysis Technique

Authors

  • Sunil Kumar Kashyap School of Advanced Sciences, Vellore Institute of Technology University, Vellore, Tamil Nadu
  • Swati Jain Government Engineering College, Raipur, Chhattisgarh, India
  • Vikas Kumar Jain Pandit Ravishankar Shukla University, Raipur, Chhattisgarh, India

DOI:

https://doi.org/10.37628/jeset.v5i1.1093

Abstract

ABSTRACT Compactness of the Fuzzy Logic (FL), Artificial Neural Network (ANN) and Genetic Algorithm (GA) is applied to analyze the data. This paper presents a foundation for the same in compact form over the Sylvester’s Law of Inertia (SLI). The sequence of FL, ANN and GA is studied for deciding the source of output data. The data interacts with the academic institutes. The academic planning is based on the existed data. Thus, its characteristic is required precisely. The proposed technique provides the layers of optimized data for the further decision. FL set the data according to the membership function. The data generalizes by the ANN. Finally, GA constructs a new decision system based on multiple layers of selection, crossover and mutation. Keywords: FL, ANN, GA, SLI. Cite this Article: Swati Jain, Vikas Kumar Jain, Sunil Kumar Kashyap. Fuzzy Logic, Artificial Neural Network and Genetic Algorithm over Sylvester Law of Inertia based Data Analysis Technique. International journal of Embedded Systems and Emerging Technologies. 2019; 5 (1): 22–29p.

Author Biography

  • Sunil Kumar Kashyap, School of Advanced Sciences, Vellore Institute of Technology University, Vellore, Tamil Nadu
    Department of Mathematics

Published

2019-07-19

Issue

Section

Articles