Modeling the City Distribution System Reliability with Bayesian Networks to Identify Influence Factors

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="9"><hr/></td></tr><tr class="thead"><td class="align_left">Joint conditional probability</td><td class="align_center"><i>ABC</i></td><td class="align_center"><span style="width: 25.8318ptpx;"><svg height="12.1044pt" id="M78" style="vertical-align:-0.2062998pt" version="1.1" viewbox="-0.0498162 -11.8981 25.8318 12.1044" width="25.8318pt" 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="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><rect height="0.65243" width="7.84228" x="9.13486" y="-11.1958"></rect><g 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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(.013,0,0,-0.013,9.173,0)"><path d="M578 512C578 619 494 650 387 650H140L134 622C219 615 223 609 210 542L127 119C112 40 104 34 23 28L17 0H235C317 0 387 7 444 33C515 65 564 122 564 195C564 289 495 335 412 352V354C505 373 578 422 578 512ZM486 510C486 422 423 367 314 367H257L294 565C299 591 305 602 315 608C324 614 339 617 362 617C421 617 486 595 486 510ZM466 200C466 100 393 35 296 35C222 35 198 51 212 127L250 333H303C388 333 466 303 466 200Z" id="g113-67"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="601" vert-adv-y="601"></glyph.data></g><rect height="0.65243" width="8.71657" x="16.9865" y="-11.1958"></rect><g transform="matrix(.013,0,0,-0.013,16.986,0)"><path d="M645 631C614 643 545 666 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18 122 136 122 287C122 464 244 632 435 632C544 632 602 595 608 472L639 475C643 526 645 581 645 631Z" id="g113-68"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="668" vert-adv-y="668"></glyph.data></g></svg></span></td><td class="align_center"><span style="width: 30.19ptpx;"><svg height="12.1044pt" id="M84" style="vertical-align:-0.2062998pt" version="1.1" viewbox="-0.0498162 -11.8981 30.19 12.1044" width="30.19pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><rect height="0.65243" width="9.17327" x="0" y="-11.1958"></rect><g transform="matrix(.013,0,0,-0.013,0,0)"><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><rect 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204 526L125 122C110 43 105 36 24 27L17 0H250C382 0 482 23 571 76C680 141 743 248 743 375ZM644 379C644 188 520 36 305 36C277 36 249 38 229 46C205 55 202 71 212 126L293 553C300 588 306 600 317 606C330 613 356 617 390 617C547 617 644 537 644 379Z" id="g113-69"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="766" vert-adv-y="766"></glyph.data></g></svg></span></td><td class="align_center">0.01</td><td class="align_center">0.37</td><td class="align_center">0.33</td><td class="align_center">0.28</td><td class="align_center">0.59</td><td class="align_center">0.63</td><td class="align_center">0.79</td><td class="align_center">0.98</td></tr><tr class="table-tr"><td colspan="9"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Joint probability between the hardware configuration and its parent.

Scientific Programming

tab3

Table 3

Table 3: Modeling the City Distribution System Reliability with Bayesian Networks to Identify Influence Factors 