A Novel Intelligent Method for Predicting the Penetration Rate of the Tunnel Boring Machine in Rocks

<div>The detailed search process of the particles in the RVM-PSO model established for predicting the TBM penetration rate in the Queens Water Tunnel <span class="nowrap"><svg height="8.55521pt" id="M86" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -8.34882 12.6264 8.55521" width="12.6264pt" 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="M448 453H361L394 608H355L322 453H214L248 608H210L176 453H79L70 395H163L134 259H35L24 201H120L82 27H120L158 201H266L229 27H267L305 201H395L404 259H318L348 395H439L448 453ZM310 395L280 259H173L202 395H310Z"></path></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><path d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z"></path></g></svg>.</span></div>

Mathematical Problems in Engineering

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Figure 4

Figure 4: A Novel Intelligent Method for Predicting the Penetration Rate of the Tunnel Boring Machine in Rocks 