Online Missing Data Imputation Using Virtual Temporal Neighbor in Wireless Sensor Networks

<div>The relationship between parameter <svg height="9.49473pt" id="M188" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -9.28833 6.59789 9.49473" width="6.59789pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M475 507C475 612 440 712 326 712C139 712 23 420 23 215C23 96 58 -12 180 -12C369 -12 475 293 475 507ZM391 522C391 486 387 448 379 394H126C155 538 222 677 310 677C386 677 391 571 391 522ZM373 346C344 193 283 22 189 22C126 22 106 114 106 196C106 243 111 293 118 346H373Z"></path></g></svg> and performance of VTN algorithm. (a) RMSE and 𝜃. (b) Computational time and 𝜃.</div>

Wireless Communications and Mobile Computing

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Figure 5

Figure 5: Online Missing Data Imputation Using Virtual Temporal Neighbor in Wireless Sensor Networks 