Prescriptive Analytics: Optimization and Modeling

Nursah Alkan; Kenan Menguc; Özgür Kabak

doi:10.1007/978-3-030-93823-9_9

Prescriptive Analytics: Optimization and Modeling

Nursah Alkan
, Kenan Menguc
, Özgür Kabak^*

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Bölüm › bilirkişi

Özet

Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted future using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Springer Series in Advanced Manufacturing
Yayınlayan	Springer Nature
Sayfalar	239-264
Sayfa sayısı	26
DOI'lar	https://doi.org/10.1007/978-3-030-93823-9_9
Yayın durumu	Yayınlandı - 2022

Yayın serisi

Adı	Springer Series in Advanced Manufacturing
ISSN (Basılı)	1860-5168
ISSN (Elektronik)	2196-1735

Bibliyografik not

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Belgeye Erişim

10.1007/978-3-030-93823-9_9

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Prescriptive Analytics: Optimization and Modeling",

abstract = "Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted future using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.",

author = "Nursah Alkan and Kenan Menguc and {\"O}zg{\"u}r Kabak",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

year = "2022",

doi = "10.1007/978-3-030-93823-9\_9",

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TY - CHAP

T1 - Prescriptive Analytics

T2 - Optimization and Modeling

AU - Alkan, Nursah

AU - Menguc, Kenan

AU - Kabak, Özgür

PY - 2022

Y1 - 2022

N2 - Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted future using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.

AB - Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted future using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.

UR - https://www.scopus.com/pages/publications/85151569016

U2 - 10.1007/978-3-030-93823-9_9

DO - 10.1007/978-3-030-93823-9_9

M3 - Chapter

AN - SCOPUS:85151569016

T3 - Springer Series in Advanced Manufacturing

SP - 239

EP - 264

BT - Springer Series in Advanced Manufacturing

PB - Springer Nature

ER -

Prescriptive Analytics: Optimization and Modeling

Özet

Yayın serisi

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap