SVM Based Event Detection and Identification: Exploiting Temporal Attribute Correlations Using SensGru

<div>Number of subregions in <svg height="9.04777pt" id="M459" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 9.65971 9.04777" width="9.65971pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M686 28C612 35 607 44 591 112C563 234 541 360 519 489L489 666L457 658L147 121C100 40 89 36 24 28L17 0H240L250 28C168 34 159 41 190 101L262 237H482C495 180 503 137 510 91C517 47 514 35 441 28L433 0H677L686 28ZM475 280H285L429 541H431L475 280Z" id="g113-66"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="703" vert-adv-y="703"></glyph.data></g></svg> and <svg height="11.9661pt" id="M460" style="vertical-align:-0.04979992pt" version="1.1" viewbox="-0.0498162 -11.9163 13.5943 11.9661" width="13.5943pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M686 28C612 35 607 44 591 112C563 234 541 360 519 489L489 666L457 658L147 121C100 40 89 36 24 28L17 0H240L250 28C168 34 159 41 190 101L262 237H482C495 180 503 137 510 91C517 47 514 35 441 28L433 0H677L686 28ZM475 280H285L429 541H431L475 280Z" id="g113-66"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="703" vert-adv-y="703"></glyph.data></g><g transform="matrix(.0095,0,0,-0.0095,9.52,-5.984)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z" id="g50-31"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="361" vert-adv-y="361"></glyph.data></g></svg> for a fixed area.</div>

Mathematical Problems in Engineering

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Figure 7

Figure 7: SVM Based Event Detection and Identification: Exploiting Temporal Attribute Correlations Using SensGru 