Canonical PSO Based <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.06579971pt" id="M1" height="11.9431pt" version="1.1" viewBox="-0.0657574 -11.8773 13.6842 11.9431" width="13.6842pt"><g transform="matrix(.018,0,0,-0.018,0,0)"><path id="g113-76" d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z"/></g></svg>-Means Clustering Approach for Real Datasets

<table class="table-group" id="tab9"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td align="center" colspan="6">ANOVA table</td></tr><tr class="thead"><td align="left">Source</td><td align="center">SS</td><td align="center">df</td><td align="center">MS</td><td align="center"><span style="width: 8.35422ptpx;"><svg height="9.04777pt" id="M162" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 8.35422 9.04777" width="8.35422pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M584 650H137L131 622C214 614 217 612 200 521L125 127C109 41 101 35 23 28L17 0H288L294 28C201 35 193 42 209 128L242 309H348C440 309 442 300 443 226H471L510 422H482C452 354 449 348 357 348H251L295 575C302 609 304 615 338 615H426C502 615 517 604 526 581C534 560 536 524 537 492L565 494C574 554 583 631 584 650Z" id="g113-71"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="607" vert-adv-y="607"></glyph.data></g></svg></span></td><td align="center">Prob &gt; <svg height="9.04777pt" id="M163" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 8.35422 9.04777" width="8.35422pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M584 650H137L131 622C214 614 217 612 200 521L125 127C109 41 101 35 23 28L17 0H288L294 28C201 35 193 42 209 128L242 309H348C440 309 442 300 443 226H471L510 422H482C452 354 449 348 357 348H251L295 575C302 609 304 615 338 615H426C502 615 517 604 526 581C534 560 536 524 537 492L565 494C574 554 583 631 584 650Z" id="g113-71"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="607" vert-adv-y="607"></glyph.data></g></svg></td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td align="left">Columns</td><td align="center">0.0323</td><td align="center">4</td><td align="center">0.00807</td><td align="center" rowspan="3">176.91</td><td align="center" rowspan="3"><span style="width: 81.6163ptpx;"><svg height="9.06134pt" id="M164" style="vertical-align:-0.3625803pt" version="1.1" viewbox="-0.0498162 -8.69876 81.6163 9.06134" width="81.6163pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z" id="g113-50"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,6.503,0)"><path d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z" id="g113-47"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="228" vert-adv-y="228"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,9.592,0)"><path d="M456 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130 -12 237 -12C322 -12 435 52 435 169C435 256 372 304 303 343C349 374 375 398 383 407C401 429 411 458 411 487C411 569 344 635 249 635ZM238 603C285 603 337 567 337 482C337 422 310 385 276 358C205 393 145 426 145 500C145 552 179 603 238 603ZM248 20C183 20 125 70 125 163C125 218 158 268 206 300C284 261 355 217 355 143C355 66 308 20 248 20Z" id="g113-57"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,42.11,0)"><path d="M391 364C391 409 353 448 295 448C249 448 198 426 152 393C65 331 23 225 23 139C23 14 96 -12 146 -12C198 -12 280 9 367 101L351 124C300 78 242 48 194 48C129 48 109 107 109 162V191C208 213 391 266 391 364ZM313 350C313 305 268 261 113 223C132 334 187 381 217 398C227 404 244 405 261 405C290 405 313 385 313 350Z" id="g113-102"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="414" vert-adv-y="414"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,50.747,0)"><path d="M535 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338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z" id="g113-54"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g></svg></span></td></tr><tr><td align="left">Error</td><td align="center">0.00023</td><td align="center">5</td><td align="center">0.00005</td></tr><tr><td align="left">Total</td><td align="center"><b>0.03253</b></td><td align="center"><b>9</b></td><td align="center"> </td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

ANOVA 1 test for <svg height="9.04777pt" id="M159" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 10.3669 9.04777" width="10.3669pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z" id="g113-76"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="755" vert-adv-y="755"></glyph.data></g></svg>-means, DBSCAN, Hierarchical, simple PSO based <svg height="9.04777pt" id="M160" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 10.3669 9.04777" width="10.3669pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z" id="g113-76"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="755" vert-adv-y="755"></glyph.data></g></svg>-means, and Canonical PSO based <svg height="9.04777pt" id="M161" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.99795 10.3669 9.04777" width="10.3669pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z" id="g113-76"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="755" vert-adv-y="755"></glyph.data></g></svg>-means algorithm on air pollution dataset.

International Scholarly Research Notices

tab9

Table 9

Table 9: Canonical PSO Based <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.06579971pt" id="M1" height="11.9431pt" version="1.1" viewBox="-0.0657574 -11.8773 13.6842 11.9431" width="13.6842pt"><g transform="matrix(.018,0,0,-0.018,0,0)"><path id="g113-76" d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z"/></g></svg>-Means Clustering Approach for Real Datasets 

International Scholarly Research Notices

Canonical PSO Based -Means Clustering Approach for Real Datasets

Table 9