UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Unique Identifier

Published Paper ID:
JETIR1902744


Registration ID:
197532

Page Number

288-290

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Title

Influential parameters on rainfall forecasting using multiple linear regression

Abstract

In this study, the function of Multiple linear regression is used to find the influential parameters on rainfall forecasting. The algorithm is applied on the dataset to determine importance of input parameters on the target variable. The input parameters include humidity, temperature, cloud amount, wind speed and surface pressure. The regression model was evaluated statistically with R2, adjusted R2, p-value and residual standard error values.

Key Words

Multiple linear regression, Meteorological Data.

Cite This Article

"Influential parameters on rainfall forecasting using multiple linear regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.288-290, February-2019, Available :http://www.jetir.org/papers/JETIR1902744.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Influential parameters on rainfall forecasting using multiple linear regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp288-290, February-2019, Available at : http://www.jetir.org/papers/JETIR1902744.pdf

Publication Details

Published Paper ID: JETIR1902744
Registration ID: 197532
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier):
Page No: 288-290
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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