Big Data Management by Fuzzy, Neural Network and Genetic Algorithm
Anil Kumar Tiwari1, G. Ramakrishna2, Lokesh Kumar Sharma3, Sunil Kumar Kashyap4
1Anil Kumar Tiwari, Department of Computer Science, KL University, Vijayavada, Andhra Pradesh, India.
2G. Ramakrishna, Department of Computer Science, KL University, Vijayavada, Andhra Pradesh, India.
3Lokesh Kumar Sharma, National Institute of Occupational Health, Ahemdabad, India.
4Sunil Kumar Kashyap, Department of Mathematics, School of Advanced Sciences, VIT University, Vellore, Tamil Nadu, India.
Manuscript received on March 10, 2017. | Revised Version Manuscript Received on March 15, 2017. | Manuscript published on March 20, 2017. | PP: 27-28 | Volume-4 Issue-5, March 2017. | Retrieval Number: E0725034517/2017©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper manages the academic data by the dynamic techniques. The data may have the infinite information. This infinite information transforms into the finite information by the dynamic algorithm. This dynamic algorithm consists fuzzy logic, neural and genetic algorithm. Thus the result lies the data analysis from Data Mining to Dynamic Data Mining. New techniques are introduced here for redefining the database and its analysis. The database Student’s Academic Performances is selected for the generalization of the proposed method. It is all is studied over Fuzzy, Neural Network and Genetic Algorithm
Keywords: Data Mining (DM), Dynamic Data Mining (DDM), Database (DB), Student’s Academic Performance (SAP), Neural Network (NN), Genetic Algorithm (GA).