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Short term wind speed prediction based on evolutionary support vector regression algorithms.html
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<title data-react-helmet="true">Short term wind speed prediction based on evolutionary support vector regression algorithms - ScienceDirect</title>
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data-reactid="134">https://doi.org/10.1016/j.eswa.2010.09.067</a><a class="rights-and-content" target="_blank" href="https://s100.copyright.com/AppDispatchServlet?publisherName=ELS&contentID=S0957417410010249&orderBeanReset=true" data-reactid="135">Get rights and content</a></div><!-- react-empty: 136 --><section class="ReferencedArticles" data-reactid="137"></section><section class="ReferencedArticles" data-reactid="138"></section><div class="PageDivider" data-reactid="139"></div><div class="Abstracts" data-reactid="140"><div class="abstract author" id="aep-abstract-id10" lang="en" data-reactid="141"><h2 data-reactid="142">Abstract</h2><div id="aep-abstract-sec-id11" data-reactid="143"><p id="sp010" data-reactid="144">Hyper-parameters estimation in regression Support Vector Machines (SVMr) is one of the main problems in the application of this type of algorithms to learning problems. This is a hot topic in which very recent approaches have shown very good results in different applications in fields such as bio-medicine, manufacturing, control, etc. Different evolutionary approaches have been tested to be hybridized with SVMr, though the most used are evolutionary approaches for continuous problems, such as evolutionary strategies or particle swarm optimization algorithms. In this paper we discuss the application of two different evolutionary computation techniques to tackle the hyper-parameters estimation problem in SVMrs. Specifically we test an Evolutionary Programming algorithm (EP) and a Particle Swarm Optimization approach (PSO). We focus the paper on the discussion of the application of the complete evolutionary-SVMr algorithm to a real problem of wind speed prediction in wind turbines of a Spanish wind farm.</p></div></div><div class="abstract graphical" id="aep-abstract-id8" lang="en" data-reactid="145"><div id="aep-abstract-sec-id9" data-reactid="146"><h3 data-reactid="147">Research highlights</h3><p id="sp005" data-reactid="148">► In this paper we have presented an Evolutionary-SVM algorithm for a problem of short-term wind speed forecast. ► We show that evolutionary algorithms such as Evolutionary Programming or Particle Swarm optimization can be used to successfully obtain the parameters of SVMs. ► The evolutionary-SVM approach obtains very high quality solutions to the problem of short-term wind speed forecast, as we have shown in real data from a wind farm in Spain.</p></div></div></div><!-- react-empty: 149 --><div class="Keywords" data-reactid="150"><div class="keyword-section" id="aep-keywords-id12" data-reactid="151"><h2 class="keyword-title" data-reactid="152">Keywords</h2><div class="keyword" data-reactid="153"><span data-reactid="154">Support vector regression algorithms</span></div><div class="keyword" data-reactid="155"><span data-reactid="156">Evolutionary algorithms</span></div><div class="keyword" data-reactid="157"><span data-reactid="158">Hyper-parameters estimation</span></div><div class="keyword" data-reactid="159"><span data-reactid="160">Short-term wind speed forecasting</span></div></div></div><!-- react-text: 161 --><!-- /react-text --><!-- react-empty: 162 --><!-- react-empty: 163 --><div class="related-content-links show-t-s hide-t hide-l hide-d" data-reactid="164"><div data-reactid="165"><div class="RelatedContentLink" data-reactid="166">Recommended articles</div><div class="RelatedContentLink" data-reactid="167">Citing articles (0)</div></div></div><!-- react-empty: 168 --><!-- react-empty: 169 --><div class="References" data-reactid="170"></div><!-- react-empty: 171 --><!-- react-empty: 172 --><!-- react-empty: 173 --><!-- react-empty: 174 --><div class="Copyright" data-reactid="175"><span class="copyright-line" data-reactid="176">Copyright © 2010 Elsevier Ltd. 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