ROBUST FUZZY NEURO SYSTEM FOR BIG DATA ANALYTICS

Article Sidebar

PDF
Published: Aug 28, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i7.4164
Keywords:
ANFIS, Fuzzy System, Membership Function, Neural System, Uncertainty

Main Article Content

Aman taneja
University Institute of technology
http://orcid.org/0000-0003-2614-9527
Kamna Solanki
UIET, MDU
Dr. Sandeep Dalal
DCSA, MDU

Abstract

Big Data is the relationship of data size and its processing speed. These are so big and complex that traditional data processing software is inadequate. These days it’s a high challenge to construct architecture to take out information cost-effectively from huge, volume of data at remarkable rate. So, there is a need to find economical and valuable solutions for the major challenges of fatly growing volume and concern. Through this paper, we can become proficient in big data analytics, its tools and application areas. It also presents uncertainty issues related to Big Data for which the solution we provided by combining fuzzy and neural network concepts to assemble a new intelligent system ANFIS that has brought together tendency to get the results by relating knowledge representation, uncertainty and modeling the key feature of big data to provide a superlative solution.

Downloads

Download data is not yet available.

Article Details

Issue
Vol. 8 No. 7 (2017): July-August 2017
Section
Articles

COPYRIGHT

Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
  • The journal allows the author(s) to retain publishing rights without restrictions.
  • The journal allows the author(s) to hold the copyright without restrictions.
Author Biographies

Aman taneja, University Institute of technology

Computer Science & Engineering

Kamna Solanki, UIET, MDU

Computer Science & Engneering

References

. M. Vijayalakshmi, " Big Data Analytics Frameworks Parth Chandarana" , International Conference on Circuits, Systems, Communication and Information Technology Applications,(CSCITA),DOI: 10.1109/CSCITA.2014.6839299

. Amir Gandomi, Murtaza Haider,Ted Rogers, “Beyond the hype: Big data concepts, methods, and analyticsâ€, International Journal of Information Management, 0268-4012/© 2014.

. B. Saraladevia, N. Pazhanirajaa, P. Victer Paula, M.S. Saleem Bashab, P. Dhavachelvanc, “Big Data and Hadoop-A Study in Security Perspectiveâ€,2nd International Symposium on Big Data and Cloud Computing (ISBCC’15)

. Xue Qin,Brian Kelley,Mahdy Saedy, “A Fast Map-Reduce Algorithm for Burst Errors in Big Data Cloud Storageâ€, 10th System of Systems Engineering Conference (SoSE) 2015 978-1-4799-7611-9/15/$31.00 ©2015 IEEE

.Fazal-e-Amin, Abdullah S. Alghamdi, Iftikhar Ahmad, Tazar Hussain,†Big Data for C4I Systems: Goals, Applications, Challenges and Tools†Fifth international conference on Innovative Computing Technology, 978-1-4673-7551-1/ 15/$31.00© 2015 IEEE

. U. Selvi, Dr. S. Pushpa, “ A Review of Big Data and Anonymization Algorithmsâ€, International Journal of Applied Engineering Research ISSN 0973-4562 Volume 10, Number 17 (2015)

. J. Dean and S. Ghemawat, “Mapreduce: simplified data processing on large clusters,†Commun. ACM, vol. 51, pp. 107–113, January 2008

. “Apache hadoop.†http://en.wikipedia.org/wiki/Apache Hadoop.

. “Yahoo hadoop tutorial.†http://public.yahoo.com/gogate/

hadoop-tutorial/starttutorial.html.

. S. Manoharan, “Effect of task duplication on the assignment of dependency graphs,†Parallel Comput., vol. 27, pp. 257–268, February 2001.

. Dr. Siddaraju1, Sowmya C L2, Rashmi K3, Rahul M, “Efficient Analysis of Big Data Using Map Reduce Framework “, International Journal of Recent Development in Engineering and Technology ISSN 2347-6435(Online) Volume 2, Issue 6, June 2014

. Hadoop Distributed File System (HDFS), http://hortonworks.com/hadoop/

. B.Tulasi, “ Significance of Big Data and Analytics in Higher Educationâ€, International Journal of Computer Applications (0975 – 8887) Volume 68– No.14, April 2013

. Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung. The Google _le system. In 19th Symposium on Operating Systems Principles, pages 29.43, Lake George,

New York, 2003.

. S.Sangeetha, A.K Sreeja, “Science No Humans, No New Technologies No changes "Big Data a Great Revolution"â€, S.Sangeetha et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (4) , 2015, 3269-3274

. Big Data for C4I Systems: Goals, Applications,Challenges and Tools Fazal-e-Amin, Abdullah S. Alghamdi, Iftikhar Ahmad, Tazar Hussain, Fifth international conference on Innovative Computing Technology (INTECH 2015) 978-1-4673-7551-1/15/$31.00© 2015 IEEE

. Hajar Mousanif,Hasna Sabah, Yasmina Douiji, Younes Oulad Sayad OSER, “From Big Data to Big Projects: a Step-by-step Roadmapâ€, 2014 International Conference on Future Internet of Things and Cloud 978-1-4799-4357-9/14 $31.00 © 2014 IEEE DOI 10.1109/FiCloud.2014.66

.http://in.mathworks.com/matlabcentral/fileexchange/29043-neuro-fuzzy-classifier

. F. Barouni, *, B. Moulin, "An Intelligent Atial Proximity System Using Neurofuzzy Classifiers And Contextual Information "

The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences, Volume Xl-2, 2014 Isprs Technical Commission Ii Symposium, 6 – 8 October 2014

. A. Abraham ,Adaptation of Fuzzy Inference System

Using Neural Learning,Chapter 3 http://ajith.softcomputing.net

. Shubhangi G. Khadse, “A Survey of Data Uncertainty in Face Recognition “,International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014, 7623-7625