{"id":12293,"date":"2023-05-28T15:06:58","date_gmt":"2023-05-28T12:06:58","guid":{"rendered":"https:\/\/bestessayhomework.com\/tr\/?p=12293"},"modified":"2023-05-28T15:06:58","modified_gmt":"2023-05-28T12:06:58","slug":"rasgele-arama-olasiligi","status":"publish","type":"post","link":"https:\/\/bestessayhomework.com\/tr\/rasgele-arama-olasiligi\/","title":{"rendered":"Rasgele Arama Olas\u0131l\u0131\u011f\u0131"},"content":{"rendered":"

Rasgele Arama Olas\u0131l\u0131\u011f\u0131<\/span><\/strong><\/h3>\n

Rasgele arama olas\u0131l\u0131\u011f\u0131, qKj \u00f6zyinelemeli arama olas\u0131l\u0131\u011f\u0131 ve Kj hedef makalenin at\u0131f say\u0131s\u0131d\u0131r. Bu nedenle, tercihli ba\u011flanma mekanizmas\u0131n\u0131n mikroskobik bir gerek\u00e7esi olarak uzun s\u00fcre azalt\u0131ld\u0131 ve uzun s\u00fcre kabul edildi.<\/span><\/p>\n

Bununla birlikte, t\u00fcretilmesinin \u00e7ok basitle\u015ftirici varsay\u0131mlara dayand\u0131\u011f\u0131na dikkat edin: t\u00fcm ka\u011f\u0131tlar\u0131n rastgele se\u00e7ilme olas\u0131l\u0131\u011f\u0131 ayn\u0131d\u0131r, rastgele bulunan ka\u011f\u0131d\u0131n yaln\u0131zca bir atas\u0131 yeni bir ka\u011f\u0131t taraf\u0131ndan se\u00e7ilir, eskime ve haf\u0131za yoktur.<\/span><\/p>\n

Bu varsay\u0131mlardan, ya\u015flanman\u0131n olmamas\u0131 t\u00fcretilmesi i\u00e7in \u00e7ok \u00f6nemlidir. Eskimenin varl\u0131\u011f\u0131nda, \u00f6zyinelemeli arama mekanizmas\u0131, \u0394Kj’nin (t – \u0394) t , t – \u0394 zaman penceresinde ka\u011f\u0131t taraf\u0131ndan toplanan al\u0131nt\u0131lar\u0131n say\u0131s\u0131 oldu\u011fu ve \u0394’n\u0131n karakteristik bellek s\u00fcresi oldu\u011fu yerde verir. \u00d6nceki b\u00f6l\u00fcmlerde g\u00f6sterdi\u011fimiz gibi, makalelerin al\u0131nt\u0131 dinami\u011fini daha ger\u00e7ek\u00e7i bir \u015fekilde yakalar. Ancak bu denklem, \u00f6zellikle k\u0131sa \u0394 i\u00e7in tercihli ba\u011flanma modelinden \u00e7ok farkl\u0131d\u0131r.<\/span><\/p>\n

Bu kitapta, uygunluk temelli aramay\u0131 yinelemeli aramaya yerle\u015ftiren ve al\u0131nt\u0131 a\u011f\u0131n\u0131n ya\u015flanmas\u0131n\u0131, haf\u0131zas\u0131n\u0131 ve topolojisini do\u011fru bir \u015fekilde dikkate alan ger\u00e7ek\u00e7i bir al\u0131nt\u0131 dinamikleri modeli g\u00f6sterdik.<\/span><\/p>\n

Asl\u0131nda, geli\u015ftirilen \u00f6zyinelemeli arama algoritmas\u0131n\u0131n kemiklerine daha fazla a\u011f\u0131rl\u0131k verdik ve onu bilimsel makalelerin al\u0131nt\u0131 dinamiklerini hesaba katmak i\u00e7in nicel bir araca d\u00f6n\u00fc\u015ft\u00fcrd\u00fck. Modelimiz, fitness modelini ve tercihli ba\u011flanma modelini (haf\u0131zayla da olsa, a\u015fa\u011f\u0131daki yakla\u015f\u0131m\u0131) birle\u015ftirir.<\/span><\/p>\n

Bu model, yazar\u0131n referans listesini olu\u015ftururken izledi\u011fi makul bir algoritma varsayar. Modelimiz tercihli eki varsaymasa da, bu model taraf\u0131ndan olu\u015fturulan al\u0131nt\u0131 dinamikleri, uygunluk temelli t\u00fcm modellerde oldu\u011fu gibi takip eder.<\/span><\/p>\n

Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131 bunu olduk\u00e7a inand\u0131r\u0131c\u0131 bir \u015fekilde g\u00f6steriyor. Bu iki rakam \u00e7ok benzer g\u00f6r\u00fcnse de, ikincisi basit bir uygunluk modeli kullan\u0131larak olu\u015fturulmu\u015f ve ilki yinelemeli arama modelimiz kullan\u0131larak olu\u015fturulmu\u015ftur. Ve her ikisi de tercihli bir ba\u011flanma modeli kullan\u0131larak \u00fcretilmi\u015f gibi g\u00f6r\u00fcn\u00fcyor.<\/span><\/p>\n

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S\u00fcrekli rastgele de\u011fi\u015fken \u00f6rnekleri<\/span>
\nAyr\u0131k Rastgele de\u011fi\u015fkenler<\/span>
\nS\u00fcrekli olas\u0131l\u0131k<\/a> da\u011f\u0131l\u0131mlar\u0131<\/span>
\nS\u00fcrekli olas\u0131l\u0131k da\u011f\u0131l\u0131m fonksiyonu \u00f6rnekleri<\/span>
\nOlas\u0131l\u0131k ve rasgele De\u011fi\u015fkenler Ders Notlar\u0131<\/span>
\nRassal de\u011fi\u015fken \u00f6rnekleri<\/span>
\n\u0130ki boyutlu rasgele de\u011fi\u015fkenler<\/span>
\nRassal de\u011fi\u015fken Nedir<\/span><\/p>\n

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Tercihli Ba\u011flanma ve Uygunluk Modelleri Aras\u0131ndaki E\u015fde\u011ferlik<\/span><\/strong><\/h3>\n

Hem Caldarelli hem de Bianconi-Barabasi uygunluk modelleri, d\u00fc\u011f\u00fcm\u00fcn kalitesini\/benzerli\u011fini yakalarken, matematiksel olarak farkl\u0131d\u0131rlar. Ger\u00e7ekten de, Bianconi-Barabasi’nin zindeli\u011fi, tercihli ba\u011flanman\u0131n \u00fcst\u00fcne eklenirken, Caldarelli’nin zindeli\u011finin tercihli ba\u011flanma ile hi\u00e7bir ilgisi yoktur.<\/span><\/p>\n

Bununla birlikte, sadece uygunluk modelinin bir anlamda klasik tercihli ba\u011flanma modeline e\u015fde\u011fer oldu\u011funu iddia ediyoruz.<\/span>\u00a0Bu denkli\u011fi g\u00f6stermek i\u00e7in, buna g\u00f6re b\u00fcy\u00fcyen karma\u015f\u0131k bir a\u011f ele al\u0131yoruz.<\/span><\/p>\n

Her d\u00fc\u011f\u00fcm, kalan belirli bir uygunluk \u03b7 ile donat\u0131lm\u0131\u015ft\u0131r.<\/span>\u00a0D\u00fc\u011f\u00fcm\u00fcn \u00f6mr\u00fc boyunca sabittir. Bu uygunluk uygunluk da\u011f\u0131l\u0131m\u0131 \u03c1(\u03b7)’den al\u0131n\u0131r, burada \u221e \u03c1(\u03b7)d\u03b7 = 1. Ayr\u0131ca \u0394K’nin, zaman penceresi (t , t + \u0394t ) s\u0131ras\u0131nda bir d\u00fc\u011f\u00fcm taraf\u0131ndan 0 toplanan yeni kenarlar\u0131n say\u0131s\u0131 oldu\u011funu varsay\u0131yoruz. Poisson da\u011f\u0131l\u0131m\u0131, \u03bb\u0394K e\u2212\u03bb ile temsil edilir.<\/span><\/p>\n

D\u00fc\u011f\u00fcm\u00fcn uygunlu\u011fu \u03b7 taraf\u0131ndan belirlenir. A(t) normalle\u015ftirilmi\u015f ya\u015flanma fonksiyonudur. Bu k\u0131s\u0131tlama alt\u0131nda uygunluk \u03b7, d\u00fc\u011f\u00fcm\u00fcn uzun zaman s\u0131n\u0131r\u0131ndaki derecesidir, yani \u03b7 \u2248 K\u221e.<\/span><\/p>\n

Bu ifade, K0 = 1 ve \u03b5 = 0’dan ba\u015fka bir \u015fey de\u011fildir. [\u0130lgin\u00e7 bir \u015fekilde, bu t\u00fcretme, de Solla Price, K0 = 1 ba\u015flang\u0131\u00e7 varsay\u0131m\u0131n\u0131 do\u011frular.] Benzer bir sonu\u00e7 daha \u00f6nce farkl\u0131 bir yakla\u015f\u0131m kullan\u0131larak elde edilmi\u015fti.<\/span><\/p>\n

Genellikle ger\u00e7ek karma\u015f\u0131k a\u011flar\u0131n b\u00fcy\u00fcme mekanizmas\u0131n\u0131n bir de\u011ferlendirme arac\u0131 olarak kabul edilir. Burada bu denklemin ay\u0131rt edici olmad\u0131\u011f\u0131n\u0131 ve yaln\u0131zca tercihli ba\u011flanma i\u00e7in de\u011fil, uygunluk modeli i\u00e7in de ge\u00e7erli oldu\u011funu g\u00f6steriyoruz.<\/span><\/p>\n

Burada \u03b7, ortalama referans listesi uzunlu\u011fu olan R0 ile \u00e7arp\u0131l\u0131r). Bu d\u00fc\u011f\u00fcmlerin b\u00fcy\u00fcmesini ve ya\u015flanmay\u0131 sim\u00fcle ettik.<\/span>
\nfonksiyon A(t) = 0.035t . (Sim\u00fclasyonun parametreleri, bildirildi\u011fi gibi Fizik makalelerinin \u00f6l\u00e7\u00fclen al\u0131nt\u0131 dinamiklerini taklit edecek \u015fekilde |t \u22122.4|1.3 \u015fekilde se\u00e7ildi.<\/span><\/p>\n

Zaman, t =0tot =25’ten,\u0394t =1,bu \u015fekilde ad\u0131mlarla \u00e7al\u0131\u015ft\u0131r\u0131ld\u0131.<\/span>\u00a0Bu k\u00fcmedeki her j d\u00fc\u011f\u00fcm\u00fc i\u00e7in, t zaman\u0131ndan sonra biriken toplam 0 kenar say\u0131s\u0131 olan Kj(t) ve kazan\u0131lan ek kenarlar\u0131n say\u0131s\u0131 olan \u0394Kj(t)’yi belirledik.\u00a0<\/span><\/p>\n

Her t i\u00e7in, t\u00fcm d\u00fc\u011f\u00fcmleri logaritmik olarak aral\u0131kl\u0131 40 b\u00f6lmede grupland\u0131rd\u0131k, her b\u00f6lme K’nin yak\u0131n de\u011ferlerine sahip d\u00fc\u011f\u00fcmleri i\u00e7eriyordu. Her b\u00f6lme i\u00e7in, \u0394K da\u011f\u0131l\u0131m\u0131n\u0131 belirledik ve ortalamas\u0131n\u0131, \u0394K bulduk. A, k\u00fc\u00e7\u00fck K i\u00e7in K’ye kar\u015f\u0131 \u0394K \u00e7izer. \u00d6nerildi\u011fi gibi, ortak kesi\u015fimi -1 olan d\u00fcz \u00e7izgiler g\u00f6zlemliyoruz. T\u00fcm \u0394K (K ) ba\u011f\u0131ml\u0131l\u0131\u011f\u0131na uymas\u0131 i\u00e7in a\u015fa\u011f\u0131daki denklemi kulland\u0131k.<\/span><\/p>\n

0’dan 2’ye makul \u03bc ve 1’den 2’ye \u03c3 makul de\u011ferleri i\u00e7in K0, 0,5 ile 1,5 aras\u0131ndad\u0131r. \u03c3 ve daha az \u00f6l\u00e7\u00fcde \u03bc ile belirlenir. B\u00fct\u00fcn bunlar \u015fu anlama gelir: K0, b\u00fcy\u00fck K’den ekstrapolasyon kullan\u0131larak \u00f6l\u00e7\u00fcl\u00fcrse, ki\u015fi her zaman K0 = 1 al\u0131r.<\/span><\/p>\n

\u00d6te yandan, uygunluk da\u011f\u0131l\u0131mlar\u0131n\u0131n \u00e7o\u011fu geni\u015f oldu\u011fundan, \u00e7o\u011fu \u00e7al\u0131\u015fmada genellikle yap\u0131ld\u0131\u011f\u0131 gibi k\u00fc\u00e7\u00fck K i\u00e7in yap\u0131lan tahminler K0 = 0,5\u20131,5 verir. Dar uygunluk da\u011f\u0131l\u0131m\u0131 i\u00e7in K0’\u0131n daha y\u00fcksek olabilece\u011fini g\u00f6sterir.<\/span><\/p>\n

At\u0131f dinami\u011fi \u00e7al\u0131\u015fmalar\u0131m\u0131zdan \u00e7\u0131kar\u0131lan \u00f6l\u00e7\u00fclen K0 de\u011ferlerinin grafi\u011fini \u00e7iziyoruz. \u00dc\u00e7 ara\u015ft\u0131rma alan\u0131n\u0131 ele ald\u0131k: Fizik, Ekonomi ve Matematik ve t\u00fcm bu alanlar i\u00e7in uygunluk da\u011f\u0131l\u0131mlar\u0131n\u0131n ayn\u0131 \u03c3 = 1.1 ile log-normaller oldu\u011funu bulduk. \u00d6l\u00e7\u00fclen ve hesaplanan ba\u015flang\u0131\u00e7 \u00e7ekicilikleri K0 iyi bir uyum i\u00e7indedir ve hepsi 1’e yak\u0131nd\u0131r.<\/span><\/p>\n

B\u00f6ylece say\u0131sal sim\u00fclasyonumuz, varsay\u0131ld\u0131\u011f\u0131 gibi ba\u015flang\u0131\u00e7 \u00e7ekicili\u011fi K0 \u2248 1 ile destekler. Do\u011fal soru ortaya \u00e7\u0131k\u0131yor – neden K0 \u2248 1 bu kadar yayg\u0131n? K0 \u2248 1’in \u03bc’den ba\u011f\u0131ms\u0131z olarak \u03c3 = 1\u20131,5’e kar\u015f\u0131l\u0131k geldi\u011fini g\u00f6sterir.<\/span><\/p>\n

Buna g\u00f6re b\u00fcy\u00fcyen log-normal uygunluk da\u011f\u0131l\u0131m\u0131na sahip karma\u015f\u0131k a\u011flar\u0131 incelemek i\u00e7in say\u0131sal sim\u00fclasyon kullan\u0131ld\u0131. Ortaya \u00e7\u0131kan a\u011f yap\u0131s\u0131n\u0131n, uygunluk da\u011f\u0131l\u0131m\u0131n\u0131n \u03c3 geni\u015fli\u011fine g\u00fc\u00e7l\u00fc bir \u015fekilde ba\u011fl\u0131 oldu\u011funu, \u00f6zellikle, kuvvet yasas\u0131 derecesi da\u011f\u0131l\u0131m\u0131n\u0131n yaln\u0131zca \u03c3 \u2248 1 i\u00e7in g\u00f6r\u00fcnd\u00fc\u011f\u00fcn\u00fc ve \u00fcss\u00fcn\u00fcn \u03bd 3’e yak\u0131n oldu\u011funu bulmu\u015flard\u0131r.<\/span><\/p>\n

Bu g\u00f6zlem, ba\u015flang\u0131\u00e7taki \u00e7ekicili\u011fin, uygunluk modeli \u00e7er\u00e7evesinde, K0 \u2248 1’in karma\u015f\u0131k a\u011flardaki evrenselli\u011finin, \u00e7o\u011funun sergiledi\u011fi ger\u00e7e\u011finin bir sonucu olacak \u015fekilde, derece da\u011f\u0131l\u0131m\u0131n\u0131n \u00fcss\u00fcne ba\u011fland\u0131\u011f\u0131n\u0131 ima eder.<\/span><\/p>\n

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