Advertisement

Adaptive Pre-processing and Regression of Weather Data

  • Varsha PullabhotlaEmail author
  • K. P. Supreethi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 8)

Abstract

With the evolution of data and increasing popularity of IoT (Internet of Things), stream data mining has gained immense popularity. Researchers and developers are trying to analyze data patterns obtained from various devices. Stream data have several characteristics, the most important being its huge volume and high velocity. Although, a lot of research is being conducted in order to develop more efficient stream data mining techniques, pre-processing of stream data is an area that is under-studied. Real time applications generate data which is rather noisy and contain missing values. Apart from this, there is the issue of data evolution, which is a concern when dealing with stream data. To deal with the evolution of data, the proposed solution offers a hybrid of preprocessing techniques which are adaptive in nature. As a result of the study, an adaptive preprocessing and learning approach is implemented. The case study with sensor weather data demonstrates the results and accuracy of the proposed solution.

Keywords

Stream mining Data evolution Adaptive pre-processing 

References

  1. 1.
    A. Bifet, G. Holmes, B. Pfahringer, R. Kirkby, and R. Gavalda.: New Ensemble Methods for Evolving Data Streams. In: Proc. 15th ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (KDD ’09), pp. 139–148, 2009Google Scholar
  2. 2.
    E. Ikonomovska, J. Gama, and S. Dzeroski.: Learning Model Trees from Evolving Data Streams. In: Data Mining Knowledge Discovery, vol. 23, no. 1, pp. 128–168, 2011Google Scholar
  3. 3.
    P. Kadlec and B. Gabrys.: Architecture for Development of Adaptive on-Line Prediction Models. In: Memetic Computing, vol. 1, no. 4, pp. 241–269, 2009Google Scholar
  4. 4.
    Indrė Žliobaitė and Bogdan Gabrys.: Adaptive Pre-processing for Streaming Data. In: IEEE Transactions On Knowledge And Data Engineering, Vol. 26, No. 2, February 2014Google Scholar
  5. 5.
    Ketan Desale and Roshani Ade.: Preprocessing of Streaming Data using Genetic Algorithm. In: International Journal of Computer Applications (0975–8887) Volume 120–No.17, June 2015Google Scholar
  6. 6.
    Piotr Duda, Maciej Jaworski, and Lena Pietruczuk.: On Pre-processing Algorithms for Data Stream, L. Rutkowski et al. (Eds.): ICAISC 2012, Part II, LNCS 7268, pp. 56–63, 2012. Springer-Verlag Berlin Heidelberg 2012Google Scholar
  7. 7.
    H. Ruda.: Adaptive Preprocessing for on-Line Learning with Adaptive Resonance Theory (Art) Networks. In: Proc. IEEE Workshop Neural Networks for Signal Processing (NNSP), 1995Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentJawaharlal Nehru Technological University HyderabadHyderabadIndia

Personalised recommendations