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Oct 26th, 2021
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  50.                         <h1>Machine learning techniques for predicting lightning events</h1>
  51.                         <h2 class="subheading">Researchers have used machine learning techniques to successfully avoid lightning hazards near and far by looking at observations of meteorological parameters at a single location.</h2>
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  53.                             Posted by
  54.                             <a href="#!">Ramadhan Arif H.</a>
  55.                             on October 26, 2021
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  67.                     <p>Lightning discharges in the atmosphere owe their existence to a combination of complex dynamic
  68.                         and microphysical processes. Knowledge discovery and data mining methods can be used to search
  69.                         for data characteristics and their teleconnections in complex data sets. Researchers have used
  70.                         machine learning techniques to successfully avoid lightning hazards near and far by looking at
  71.                         observations of meteorological parameters at a single location. The resulting alerts are
  72.                         validated using data from the lightning location system.</p>
  73.                     <p> In addition to discussing the predictive ability of the model, data mining techniques are also
  74.                         used to compare data distribution patterns, both spatially and temporally between stations. The
  75.                         results prompt further analysis of how mining techniques can contribute to a better
  76.                         understanding of lightning dependencies on atmospheric parameters.</p>
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  78.                         Source papers on this research were published in the journal: <a href = "https://www.nature.com/articles/s41612-019-0098-0#Abs1">Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques</a>
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