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Data Mining Techniques for Estimation of Wind Speed Using Weka

B. Hari Mallikarguna Reddy1 , S. Venkatramana Reddy2 , B. Sarojamma3

Section:Survey Paper, Product Type: Journal Paper
Volume-9 , Issue-9 , Page no. 48-51, Sep-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i9.4851

Online published on Sep 30, 2021

Copyright © B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma, “Data Mining Techniques for Estimation of Wind Speed Using Weka,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.48-51, 2021.

MLA Style Citation: B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma "Data Mining Techniques for Estimation of Wind Speed Using Weka." International Journal of Computer Sciences and Engineering 9.9 (2021): 48-51.

APA Style Citation: B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma, (2021). Data Mining Techniques for Estimation of Wind Speed Using Weka. International Journal of Computer Sciences and Engineering, 9(9), 48-51.

BibTex Style Citation:
@article{Reddy_2021,
author = {B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma},
title = {Data Mining Techniques for Estimation of Wind Speed Using Weka},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2021},
volume = {9},
Issue = {9},
month = {9},
year = {2021},
issn = {2347-2693},
pages = {48-51},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5394},
doi = {https://doi.org/10.26438/ijcse/v9i9.4851}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i9.4851}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5394
TI - Data Mining Techniques for Estimation of Wind Speed Using Weka
T2 - International Journal of Computer Sciences and Engineering
AU - B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma
PY - 2021
DA - 2021/09/30
PB - IJCSE, Indore, INDIA
SP - 48-51
IS - 9
VL - 9
SN - 2347-2693
ER -

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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.

Key-Words / Index Term

Wind speed, Zero regression, M5P, SMO regression, WEKA

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