
<h1> WINDMILL DATA ANALAYSIS </h1>


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<h3> WEBSITE LINK </h3>
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<li>  <a href="https://venkyvt7.github.io/WINDMILL_PROJECT_DATA/index.html"  > Home </a></li>



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<h3> Features </h3>
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<p> This is Website currently supporting following Features </p>


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<li> Wind speed and Wind Direction of Entered city  </li>
<li> Temprature of Entered city </li>
<li> POWER RATING Prediction using Wind Speed Data</li>

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<h3> Tools and Languages used</h3>
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<li>Front End
            <ul>  <li> HTML</li>
             <li> BOOTSTRAP</li>
              <li> CSS</li>
              <li> JAVASCRIPT </li>
               </ul>
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  <li> Back End </li>
   <ul>  <li> NodeJs</li> </ul>
   
   
   <li> Maching Learning </li>
   <ul>  <li> Python</li>
          <li> Numpy </li>
          <li> Pandas</li>
          <li> scikit-learn</li>
          
   
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<h3> Data Set Used For Prediction </h3>
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<li>  <a href="https://www.kaggle.com/theforcecoder/wind-power-forecasting"  >  Wind Power Forecasting </a></li>


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<h3> Research Paper ,articles and Journal Refered </h3>
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<li>  <a href="https://www.sciencedirect.com/science/article/abs/pii/S0925231201007020"  >  Time series forecasting using a hybrid ARIMA and neural network model </a></li>
<li>  <a href="https://www.hindawi.com/journals/mpe/2010/684742/" >  The Forecasting Procedure for Long-Term Wind Speed in the Zhangye Area  </a></li>

