Data Mining Techniques for Estimation of Wind Speed Using Weka

Authors

  • Hari Mallikarguna Reddy B Department of Statistics, S.V. University, Tirupati-517502, Andhra Pradesh, India
  • Venkatramana Reddy S Department of Physics, S.V. University, Tirupati-517502, Andhra Pradesh, India
  • Sarojamma B Department of Statistics, S.V. University, Tirupati-517502, Andhra Pradesh, India

DOI:

https://doi.org/10.26438/ijcse/v9i9.4851

Keywords:

Wind speed, Zero regressio, M5P, SMO regressio, WEKA

Abstract

Now a day’s neural network plays a vital role in analyzing, interpreting and fitting models. In this paper by taking wind speed as dependent variable and minimum temperature, maximum temperature, visibility, temperature date and time as independent variables, we fitted. M5P, SMO Regression and zero regression models and CV parameter selection criteria is also used for above three models. For computational purpose WEKA Software is used. By measures of accuracy like mean absolute error, root mean square. Relative absolute error, root relative squared error are used to select the best model and also rank them.

References

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Published

2021-09-30
CITATION
DOI: 10.26438/ijcse/v9i9.4851
Published: 2021-09-30

How to Cite

[1]
B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, and B. Sarojamma, “Data Mining Techniques for Estimation of Wind Speed Using Weka”, Int. J. Comp. Sci. Eng., vol. 9, no. 9, pp. 48–51, Sep. 2021.

Issue

Vol. 9 No. 9 (2021): IJCSE September Edition

Section

Survey Article

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