<?xml version="1.0" encoding="utf-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2d1 20170631//EN" "JATS-journalpublishing1.dtd">
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>IJIRCSTJournal</PublisherName>
      <JournalTitle>International Journal of Innovative Research in Computer Science and Technology</JournalTitle>
      <PISSN>I</PISSN>
      <EISSN>S</EISSN>
      <Volume-Issue>Volume 9 Issue 4</Volume-Issue>
      <PartNumber/>
      <IssueTopic>Computer Science and Engineering</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>July - August 2021</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>2021</Year>
        <Month>07</Month>
        <Day>19</Day>
      </PubDate>
      <ArticleType>Computer Sciences</ArticleType>
      <ArticleTitle>Prediction of Weather Forecasting by Using Machine Learning</ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>30</FirstPage>
      <LastPage>32</LastPage>
      <AuthorList>
        <Author>
          <FirstName>N. Sri Lakshmi</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
                      <FirstName>P. Ajimunnisa</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>V. Lakshmi Prasanna</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>T. YugaSravani</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>M. RaviTeja</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
           
        </Author>
      </AuthorList>
      <DOI>https://doi.org/10.21276/ijircst.2021.9.4.7</DOI>
      <Abstract>Weather forecasting has become important now a day because of varying climatic conditions around the world. Many technologies have been introduced to predict the weather whose accuracy is around 70%.Weather forecasting is used in machine learning. It is a powerful technique to predict the weather with more accuracy. Weather dataset is collected and analysed and algorithms on it to predict the weather. Using a Back Propagation Neural Network the error rate becomes less and many factors that are involved to predicting the weather gives the accurate results. To compare and evaluate the performance of above model and the programming was carried out using Visual Studio as a tool.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Classification, Weather Forecasting, Weather Conditions, Rainfall Prediction, Back Propagation Neural Network.</Keywords>
      <URLs>
        <Abstract>https://ijircst.org/abstract.php?article_id=598</Abstract>
      </URLs>      
    </Journal>
  </Article>
</ArticleSet>