Time Series Based Data Explorer and Stream Analysis for Anomaly Prediction

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Types</td><td class="align_center">Names</td><td class="align_center">Meaning</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left" rowspan="2">Flection time space</td><td class="align_center">Space-time dislocation</td><td class="align_center">Similar waveforms in two sequences present different starting moments</td></tr><tr><td class="align_center">Different duration</td><td class="align_center">The duration of similar waveforms in the two sequences is different</td></tr><tr><td class="align_left">Amplitude bending</td><td class="align_center">Amplitude misalignment</td><td class="align_center">The balance positions of similar waveforms in the two sequences are different</td></tr><tr><td class="align_left">Different amplitude</td><td class="align_center">Fluctuations of similar waveforms in the two series</td><td class="align_center">Different amplitude</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Curving phenomena in time series.</div>

Wireless Communications and Mobile Computing

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Table 1

Table 1: Time Series Based Data Explorer and Stream Analysis for Anomaly Prediction 