Data Analysis and Knowledge Mining of Machine Learning in Soil Corrosion Factors of the Pipeline Safety

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Serial number</td><td class="align_center">Soil resistivity (<span class="nowrap"><svg height="8.8423pt" id="M15" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 29.0591 8.8423" width="29.0591pt" 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="M719 146L691 147C666 77 657 72 612 72H528C572 125 688 224 688 364C688 546 558 665 384 665C212 665 77 541 77 361C77 221 188 124 239 72H150C110 72 97 80 73 147L46 146L63 0H307L314 18C284 71 178 203 178 360C178 529 256 631 383 631C509 631 588 523 588 363C588 197 485 67 453 18L458 0H701L719 146Z"></path></g><g transform="matrix(.013,0,0,-0.013,12.746,0)"><path d="M170 255C170 288 146 313 114 313S58 288 58 255C58 221 82 198 114 198S170 221 170 255Z"></path></g><g transform="matrix(.013,0,0,-0.013,18.616,0)"><path d="M766 88L752 113C719 83 690 64 681 64C674 64 672 74 679 103L724 292C758 436 724 448 701 448C680 448 666 442 639 429C594 407 514 350 441 252H439L447 289C476 423 450 448 419 448C398 448 379 441 355 427C307 400 234 344 162 249H160L180 324C203 409 197 448 170 448C144 448 82 413 23 349L35 321C57 343 96 374 108 374C115 374 117 371 111 341C87 227 57 112 24 -6L32 -12C53 -4 81 4 108 6C119 68 134 128 149 171C177 229 309 383 364 383C387 383 388 355 373 282C354 190 330 92 303 -6L309 -12C332 -4 356 3 386 6C396 63 411 122 424 171C458 236 590 383 642 383C658 383 664 369 652 315L603 91C587 20 593 -12 619 -12C642 -12 708 23 766 88Z"></path></g></svg>)</span></td><td class="align_center">Reddox potential (mV)</td><td class="align_center">Water content (%)</td><td class="align_center">Average corrosion rate (<span class="nowrap"><svg height="15.2688pt" id="M16" style="vertical-align:-3.403299pt" version="1.1" viewbox="-0.0498162 -11.8655 68.1384 15.2688" width="68.1384pt" 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="M463 437C426 431 375 425 327 422C297 440 264 449 231 449H230C153 449 51 396 51 283C51 215 94 168 139 149C123 129 91 103 51 88C50 78 53 60 62 46C75 25 100 2 136 -9C112 -28 73 -59 53 -79C38 -94 29 -113 29 -135C30 -192 91 -257 203 -257C336 -257 452 -160 452 -59C452 39 371 59 309 59C275 59 240 58 203 58C158 58 140 77 140 96C140 110 157 129 170 138C186 135 205 133 221 133C306 133 396 185 396 293C396 328 384 360 366 381L423 378C439 387 459 413 468 429L463 437ZM219 418C277 418 314 362 314 284C314 205 275 166 231 165C176 165 137 221 137 299C137 376 177 418 219 418ZM241 -11C285 -11 314 -14 339 -24C367 -36 384 -61 384 -95C384 -157 335 -206 240 -206C166 -206 108 -165 108 -110C108 -82 128 -54 154 -32C172 -17 195 -11 241 -11Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.012,0)"><path d="M170 255C170 288 146 313 114 313S58 288 58 255C58 221 82 198 114 198S170 221 170 255Z"></path></g><g transform="matrix(.013,0,0,-0.013,14.882,0)"><path d="M517 51L485 54C448 58 441 63 441 115V712C404 700 337 684 285 678V653C357 648 362 645 362 580V437C339 446 309 449 295 449C159 449 38 340 38 201C38 61 143 -12 223 -12C234 -12 261 -6 301 17L362 53V-12C420 9 495 22 517 26V51ZM362 85C338 67 301 51 266 51C201 51 128 109 128 228C128 373 212 411 259 411C296 411 338 395 362 360V85Z"></path></g><g transform="matrix(.013,0,0,-0.013,21.746,0)"><path d="M797 0V26C739 32 732 36 732 103V296C732 394 682 449 605 449C576 449 550 437 529 423C504 407 475 389 446 366C425 418 382 449 334 449C303 449 279 437 253 421C222 403 201 385 180 371V452C135 432 85 419 41 411V388C99 379 102 374 102 310V103C102 38 93 32 27 26V0H238V26C189 32 180 38 180 103V338C210 363 250 390 289 390C351 390 377 348 377 275V103C377 37 368 32 306 26V0H520V26C465 32 456 38 456 101V296C456 314 455 326 453 338C491 369 529 390 565 390C628 390 653 345 653 274V107C653 36 642 32 583 26V0H797Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,32.458,-6.016)"><path d="M556 236V289H56V236H556Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,38.019,-6.016)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g><g transform="matrix(.013,0,0,-0.013,45.891,0)"><path d="M170 255C170 288 146 313 114 313S58 288 58 255C58 221 82 198 114 198S170 221 170 255Z"></path></g><g transform="matrix(.013,0,0,-0.013,51.761,0)"><path d="M433 39L423 65C413 59 399 54 387 54C370 54 352 69 352 114V299C352 352 342 392 307 422C285 440 255 449 225 449C168 437 102 399 75 379C56 365 44 353 44 339C44 315 69 296 87 296C101 296 111 303 116 319C124 349 133 371 145 385C156 397 171 404 190 404C241 404 275 364 275 291V274C253 256 180 229 120 209C65 190 39 159 39 110C39 47 88 -12 159 -12C189 -12 237 25 277 52C282 35 288 21 301 8C312 -3 333 -12 348 -12L433 39ZM275 84C256 65 221 48 195 48C164 48 124 73 124 124C124 161 146 180 185 198C206 208 254 229 275 240V84Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,57.489,-5.741)"><path d="M556 236V289H56V236H556Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,63.049,-5.741)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg>)</span></td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">1</td><td class="align_center">255.7157 ⟶ level 2</td><td class="align_center">502.173 ⟶ level 1</td><td class="align_center">8.91 ⟶ level 3</td><td class="align_center">1.9358 ⟶ level 2</td></tr><tr><td class="align_left">2</td><td class="align_center">36.4728 ⟶ level 3</td><td class="align_center">310.531 ⟶ level 2</td><td class="align_center">33.84 ⟶ level 3</td><td class="align_center">5.4695 ⟶ level 3</td></tr><tr><td class="align_left">3</td><td class="align_center">25.7315 ⟶ level 3</td><td class="align_center">157.144 ⟶ level 3</td><td class="align_center">10.31 ⟶ level 3</td><td class="align_center">6.7316 ⟶ level 3</td></tr><tr><td class="align_left">4</td><td class="align_center">112.4932 ⟶ level 2</td><td class="align_center">422.065 ⟶ level 2</td><td class="align_center">2.27 ⟶ level 1</td><td class="align_center">3.4695 ⟶ level 2</td></tr><tr><td class="align_left">5</td><td class="align_center">28.3096 ⟶ level 3</td><td class="align_center">501.742 ⟶ level 1</td><td class="align_center">7.46 ⟶ level 2</td><td class="align_center">4.1014 ⟶ level 3</td></tr><tr><td class="align_left">6</td><td class="align_center">34.7758 ⟶ level 3</td><td class="align_center">306.683 ⟶ level 2</td><td class="align_center">20.76 ⟶ level 4</td><td class="align_center">6.1137 ⟶ level 3</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The inspection table of six groups of soil corrosion data measured in the loam area.</div>

Computational Intelligence and Neuroscience

tab5

Table 5

Table 5: Data Analysis and Knowledge Mining of Machine Learning in Soil Corrosion Factors of the Pipeline Safety 