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Refining Big Data Models to Predict the Future

  • 2018-11-21 15:15
  • 아시아뉴스통신=Ian Maclang 기자
Researchers at Spain's University of Cordoba said that big data can make an impact in predicting the future / Photo by: Rafael Jiménez via Wikimedia Commons
 

Technology has been advancing so fast, constant information has become a fundamental aspect of how society works today. This data might hold the key to predicting events that have yet to occur, with more and more of this technology making the work of specific industries more manageable and easier to do. Recently, researchers in the KIDS group of the University of Cordoba’s Department of Computer Science and Numerical Analysis found a way to improve these big data models to be able to predict more variables simultaneously based on the same set of input variables.


This new discovery means that the size of data necessary for forecasting events accurately is now reduced, thereby freeing up more time and opportunity in the process. One of the ways this can be used is to predict the different parameters of soil quality to find better ways to plant crops, and achieve more efficiency from tillage and the use of pesticides. Sebastian Ventura, a researcher and one of the authors of the article, states, “When you are dealing with a large volume of data, there are two solutions. You either increase computer performance, which is very expensive, or you reduce the quantity of information needed for the process to be done properly.” This new study essentially makes big data models much easier to use, requiring less data and only using the most relevant on a case-to-case basis. This could be massive development in this field. As Oscar Reyes, the lead author of the research, states, “We have developed a technique that can tell you which set of examples you need so that the forecast is not only reliable but could even be better.”


As the researchers of the study stated, these developments could have potential in industries like healthcare, water quality, and even environmental studies.




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