{"id":7559,"date":"2020-09-11T03:09:44","date_gmt":"2020-09-11T00:09:44","guid":{"rendered":"http:\/\/blog.ulubat.org\/?p=7559"},"modified":"2020-12-26T17:30:53","modified_gmt":"2020-12-26T14:30:53","slug":"genetik-algoritmalar","status":"publish","type":"post","link":"https:\/\/blog.ulubat.org\/index.php\/tip-ve-teknoloji\/genetik-algoritmalar\/","title":{"rendered":"GENET\u0130K ALGOR\u0130TMALAR"},"content":{"rendered":"\n
\"\"
(DNA. G\u00f6rsel Kayna\u011f\u0131: Creations\/Shutterstock<\/a>)<\/figcaption><\/figure>\n\n\n\n

Temel ilkeleri John Holland taraf\u0131ndan at\u0131lan genetik algoritma kavram\u0131, do\u011fal se\u00e7ime dayanan bir arama ve optimizasyon metodudur. Bu kavram yapay zekan\u0131n evrimsel s\u00fcre\u00e7leri inceleyip problemlere h\u0131zl\u0131 ve kolay \u00e7\u00f6z\u00fcmler \u00fcretmesi sonucu ortaya at\u0131lm\u0131\u015ft\u0131r. \u00d6rne\u011fin bir populasyonda hangi canl\u0131n\u0131n neslini s\u00fcrd\u00fcrme ihtimalinin daha y\u00fcksek oldu\u011funu belirler. Bu durum canl\u0131n\u0131n ortama uyum g\u00fcc\u00fcn\u00fcn g\u00f6stergesidir. Ayn\u0131 \u015fekilde bu populasyonun ortama adaptasyonundan daha y\u00fcksek uyum g\u00fcc\u00fcne sahip bir canl\u0131 varsa o canl\u0131 \u00e7o\u011fal\u0131r. Bu \u00e7o\u011falma logaritmiktir ve zaman ilerledik\u00e7e \u00e7o\u011falma h\u0131z\u0131 artar. Do\u011fan yeni bireyler ana-babadan daha y\u00fcksek uyum g\u00fcc\u00fcne sahiptir. <\/p>\n\n\n\n

Ortama\nadaptasyonun nesilden nesle artmas\u0131n\u0131n iki sebebi vard\u0131r:<\/p>\n\n\n\n

  1. Bir\ncanl\u0131n\u0131n uyum g\u00fcc\u00fc d\u00fc\u015f\u00fck olan bireyinin \u00fcreme h\u0131z\u0131 da d\u00fc\u015f\u00fckt\u00fcr. Bu uyum g\u00fcc\u00fc\nd\u00fc\u015f\u00fck bireyin \u00f6zelli\u011fini aktarmas\u0131 engellenir. <\/li>
  2. Genetik\nalgoritma bir canl\u0131n\u0131n iyi \u00f6zelliklerini nesilden nesle daha \u00e7ok aktar\u0131r. <\/li><\/ol>\n\n\n\n

    Genetik\nalgoritma di\u011fer algoritma t\u00fcrlerinden farkl\u0131 olarak sonsuz \u00e7\u00f6z\u00fcm uzay\u0131nda\nbirden \u00e7ok ba\u015flang\u0131\u00e7 noktas\u0131 belirler ve ku\u015faklar ilerledik\u00e7e en iyi \u00e7\u00f6z\u00fcmleri,\ndi\u011fer bir deyi\u015fle en g\u00fc\u00e7l\u00fc genleri se\u00e7er. Algoritma durunca ortaya \u00e7\u0131kan\nbireyler sonsuz \u00e7\u00f6z\u00fcm uzay\u0131nda en iyi \u00e7\u00f6z\u00fcmler olur. Kromozomlar aras\u0131\n\u00e7aprazlama yapt\u0131\u011f\u0131 i\u00e7in her bir bireyin parametrelerini inceleyerek genlerin uygunluk\nfonksiyonuna bakar. Uygunluk fonksiyon de\u011feri d\u00fc\u015f\u00fck olan genleri eleyip de\u011feri\ny\u00fcksek genleri se\u00e7er ve ebeveynden ona g\u00f6re yeni ku\u015fak do\u011far. K\u0131saca genetik\nalgoritma se\u00e7me, \u00e7aprazlama ve mutasyonu kullanarak en iyi kromozomu \u00fcretir. <\/p>\n\n\n\n

    \"\"
    (Parmak izi. G\u00f6rsel Kayna\u011f\u0131: ktsdesign\/Shutterstock<\/a>, ID:
    608453894)<\/figcaption><\/figure>\n\n\n\n

    Genetik algoritma sadece biyolojik alanlarda de\u011fil, di\u011fer meslek kollar\u0131nda da kullan\u0131labilir. Bu uygulamalar kromozomlar\u0131 dolayl\u0131 olarak i\u00e7erir. \u00d6rne\u011fin bu sene yay\u0131mlanan bir mimari \u00e7al\u0131\u015fmada kapal\u0131 bir ortamda insan\u0131n beyin sinir sistemi \u00fczerinde genetik algoritma uygulanm\u0131\u015ft\u0131r. \u00dczerinde deney yap\u0131lan ki\u015fi bulundu\u011fu i\u00e7i bo\u015f kapal\u0131 alanda bir i\u00e7 tasar\u0131m hayal etmi\u015ftir. Algoritma bireyin d\u00fc\u015f\u00fcnce ve an\u0131lar\u0131n\u0131 inceleyip insan beynine g\u00f6re en ideal ortam\u0131 yapm\u0131\u015ft\u0131r. <\/p>\n\n\n\n

    Geli\u015ftirilmi\u015f genetik algoritma bu \u00e7al\u0131\u015fmada deney yap\u0131lan ki\u015finin beynini inceleyip \u00e7ocuklar i\u00e7in en ideal s\u0131n\u0131f ortam\u0131n\u0131 yapm\u0131\u015ft\u0131r. S\u0131n\u0131f temiz ve \u00f6\u011frenmeye \u00e7ok elveri\u015fli olmu\u015ftur. Tavan, lambalar ve duvar uzay g\u00f6r\u00fcnt\u00fcs\u00fc vermi\u015ftir. Masa da s\u0131n\u0131f\u0131n merkezindedir. Bu tasar\u0131m \u00e7ocuklar\u0131n dersleri en iyi \u00f6\u011frenebilece\u011fi s\u0131n\u0131flar\u0131n basitlik \u00fczerine kurulu oldu\u011funu g\u00f6sterir. <\/p>\n\n\n\n

    Genetik algoritma mimari d\u0131\u015f\u0131nda m\u00fchendislik, bilgisayar ve ekonomi gibi alanlarda da kullan\u0131l\u0131r. Hayal ve d\u00fc\u015f\u00fcncelerimizi aktarmaya \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z bu d\u00fcnyada genetik algoritmalar ileride en iyi \u015fehirleri kurabilir, en iyi ekonomi planlar\u0131n\u0131 haz\u0131rlayabilir ve en iyi bilgisayar sistemlerini kurabilir. Bunlar\u0131n hepsi insan DNA’s\u0131nda sakl\u0131 bilgilerin yapay zeka arac\u0131l\u0131\u011f\u0131yla a\u00e7\u0131\u011fa \u00e7\u0131kmas\u0131yla yap\u0131labilir. Bu uygulamalar t\u0131bb\u0131n ya\u015fam\u0131n her alan\u0131nda kullan\u0131labilece\u011fini g\u00f6sterir. <\/p>\n\n\n\n

    Bilgi Kaynak\u00e7as\u0131<\/p>\n\n\n\n

    1. ScienceDirect. Yang, Jianfeng. \u201cIndoor space\ncompositions based on genetic algorithms to optimize neural networks\u201d Physical Communication<\/em>. (42). Ekim 2020.\n<\/li>
    2. Uluda\u011f\n\u00dcniversitesi \u0130ktisadi ve \u0130dari Bilimler Fak\u00fcltesi Dergisi. Emel, G\u00fcl G\u00f6kay. Ta\u015fk\u0131n, \u00c7a\u011fatan.\n\u201cGenetik Algoritmalar ve Uygulama Alanlar\u0131\u201d (21):1, 129-152. 2002. <\/li><\/ol>\n\n\n\n

      G\u00f6rsel Kaynak\u00e7as\u0131<\/p>\n\n\n\n

      1. Creations\/Shutterstock<\/a> <\/li>
      2. ktsdesign\/Shutterstock<\/a>, ID: 608453894<\/li><\/ol>\n\n\n\n

        <\/p>\n","protected":false},"excerpt":{"rendered":"

        Temel ilkeleri John Holland taraf\u0131ndan at\u0131lan genetik algoritma kavram\u0131, do\u011fal se\u00e7ime dayanan bir arama ve optimizasyon metodudur. Bu kavram yapay<\/p>\n","protected":false},"author":267,"featured_media":7561,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[25,20],"tags":[708,1074,226,95,73,74,894,893,106,1076,274,132,149,115,1073,810,1079,1075,76,1078,956,247,1080,873,66,1081,511],"acf":[],"views":739,"_links":{"self":[{"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/posts\/7559"}],"collection":[{"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/users\/267"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/comments?post=7559"}],"version-history":[{"count":4,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/posts\/7559\/revisions"}],"predecessor-version":[{"id":9299,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/posts\/7559\/revisions\/9299"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/media\/7561"}],"wp:attachment":[{"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/media?parent=7559"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/categories?post=7559"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.ulubat.org\/index.php\/wp-json\/wp\/v2\/tags?post=7559"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}