Skip to main content
SpringerLink
Log in

Robust Fuzzy Neuro system for Big Data Analytics

  • Conference paper
  • First Online:
Big Data Analytics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 654))

Abstract

Big Data is the name given to relationship of data size and its processing speed. These days, it is a high challenge to construct architecture to take out information economically from huge, diverse volume of data at significant rate. So, there is a need to find cost-effective and time-efficient solutions for the major challenges of fast growing volume and uncertainty. Through this paper, we can become skilled 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 accumulated characteristics to get the results by relating knowledge representation, uncertainty, and modeling the key feature of big data to provide an optimal solution. Combined intelligent system is proposed to solve complex problems in the domain of big data to give superior modeling and computation to tackle uncertainty issues.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Qin, X., Kelley, B., Saedy, M.: A fast map-reduce algorithm for burst errors in big data cloud storage. In: 10th System of Systems Engineering Conference (SoSE) (2015). 978-1-4799-7611-9/15/$31.00 ©2015 IEEE

    Google Scholar 

  2. Vijayalakshmi, M.: Big data analytics frameworks Parth Chandarana. In: International Conference on Circuits, Systems, Communication and Information Technology Applications, (CSCITA). doi: 10.1109/CSCITA.2014.6839299

  3. Fazal-e-Amin, A.K., Alghamdi, A.S., Ahmad, I., Hussain, T.: Big data for C4I systems: goals, applications, challenges and tools. In: Fifth International Conference on Innovative Computing Technology, 978-1-4673-7551-1/15/$31.00© 2015 IEEE

    Google Scholar 

  4. Ghemawat, S., Gobioff, H., Leung, S.-T.: The Google file system. In: 19th Symposium on Operating Systems Principles, pages 29.43, Lake George, New York (2003)

    Google Scholar 

  5. Gandomi, A., Haider, M., Rogers, T.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage, 0268–4012/©2014

    Google Scholar 

  6. Fazal-e-Amin, A.K., Alghamdi, A.S., Ahmad, I., Hussain, T.: Big data for C4I systems: goals, applications, challenges and tools. In: Fifth International Conference on Innovative Computing Tech(INTECH 2015) 978-1-4673-7551-1/15/$31.00© 2015 IEEE

    Google Scholar 

  7. Mousanif, H., Sabah, H., Douiji, Y., Sayad, Y.O.: From big data to big projects: a step-by-step roadmap. In: 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(OSER)

  8. Sangeetha, S., Sreeja, A.K.: Science no humans, no new technologies no changes “Big Data a Great Revolution”. (IJCSIT) Int. J. Comput. Sci. Inf. Technol. 6(4), 3269–3274 (2015)

    Google Scholar 

  9. Apache hadoop. http://en.wikipedia.org/wiki/ApacheHadoop

  10. Saraladevia, B., Pazhanirajaa, N., Victer Paula, P., Saleem Bashab, M.S., Dhavachelvanc, P.: Big data and Hadoop-A study in security perspective. In: 2nd International Symposium on Big Data and Cloud Computing (ISBCC’15)

    Google Scholar 

  11. Yahoo Hadoop Tutorial. http://public.yahoo.com/gogate/hadooptutorial/starttutorial.html

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

  13. Selvi, U., Pushpa, S.: A review of big data and anonymization algorithms, Int. J. Appl. Eng. Res. 10(17) (2015) ISSN 0973-4562

    Google Scholar 

  14. Manoharan, S.: Effect of task duplication on the assignment of dependency graphs. Parallel Comput. 27, 257–268 (2001)

    Article  MATH  Google Scholar 

  15. Siddaraju, D., Sowmya, C.L., Rashmi, K., Rahul, M.: Efficient analysis of big data using map reduce framework. Int. J. Recent Dev. Eng. Technol. 2(6). ISSN 2347-6435 (Online) (2014)

    Google Scholar 

  16. Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Commun. ACM 51, 107–113 (2008)

    Article  Google Scholar 

  17. Abraham, A.: Adaptation of fuzzy inference system using neural learning, Chapter 3. http://ajith.softcomputing.net

  18. Khadse, S.G.: A survey of data uncertainty in face recognition. Int. J. Comput. Sci. Inf. Technol. 5(6), 7623–7625 (2014)

    Google Scholar 

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

  20. Barouni, F., Moulin, B.: An intelligent atial proximity system using neurofuzzy classifiers and contextual information. In: The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences, Vol. Xl-2, 2014 Isprs Technical Commission Ii Symposium, 6–8 October 2014

    Google Scholar 

  21. Tulasi, B.: Significance of big data and analytics in higher education, Int. J. Comput. Appl. 68(14), 0975–8887 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. NCU (Formerly ITM University), Gurgaon, India

    Ritu Taneja & Deepti Gaur

Authors
  1. Ritu Taneja
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deepti Gaur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ritu Taneja .

Editor information

Editors and Affiliations

  1. Jagan Institute of Management Studies, New Delhi, Delhi, India

    V. B. Aggarwal

  2. Department of Computer Science, University of Delhi, New Delhi, Delhi, India

    Vasudha Bhatnagar

  3. Microsoft Innovation Centre, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Taneja, R., Gaur, D. (2018). Robust Fuzzy Neuro system for Big Data Analytics. In: Aggarwal, V., Bhatnagar, V., Mishra, D. (eds) Big Data Analytics. Advances in Intelligent Systems and Computing, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-10-6620-7_52

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-6620-7_52

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6619-1

  • Online ISBN: 978-981-10-6620-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation