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KİTAP DÜNYASICurrent Quantitative Decision Making Methods: Data-Driven Theory, Modeling, and Real World ApplicationsKolektif
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KİTAPLIĞINIZ İÇİN BİR KEŞİF

Current Quantitative Decision Making Methods: Data-Driven Theory, Modeling, and Real World Applications

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In today's world, decision-making processes have evolved into a more dynamic and real-time structure with big data and complex systems. Classic rule-based and inflexible traditional decision-making approaches are inadequate in the face of rapidly changing envi...

Sayfa
117
Kategori
Kitap Diğer Dildeki Yayınlar İngilizce
Yayın tarihi
2025-04-14
Yayınevi
EĞİTİM YAYINEVİ
ISBN
9786253850883
Dil
i̇ngi̇li̇z
Format
Dosya henüz eklenmedi
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Kitap hakkında

In today's world, decision-making processes have evolved into a more dynamic and real-time structure with big data and complex systems. Classic rule-based and inflexible traditional decision-making approaches are inadequate in the face of rapidly changing environmental conditions and increasing data processing speed. For this reason, data analytics and rapidly advancing artificial intelligence-supported numerical decision-making methods aim to produce more accurate results. This book aims to further clarify the issue by establishing a bridge between current theory, modeling and applications by focusing on current numerical decision-making methods. While revealing how decision-making processes can be improved with a multi-dimensional, data-supported and analytical-based approach, it also offers the reader both an academic and practical perspective by focusing on real-world problems. The chapters covered in the book are shaped on critical issues such as decision-making with multiple criteria, optimization, uncertainty management, sensitivity analysis, risk assessment and performance measurement. Innovative methods that have caught up with the current situation such as COCOFISO, ANP, CILOS, WEDBA, SV & CODAS, Monte Carlo Simulation are discussed in detail and how they can be applied in different disciplines is shown. Applications in various fields such as entrepreneurship, traffic engineering, quality of life measurement and college selection reveal the wide range of usage potential of numerical decision-making methods. This book study is actually a comprehensive reference source in terms of theory and application for academics, data analysts, business professionals and decision makers. It provides valuable insights for everyone who wants to better understand numerical decision-making techniques, make optimized strategic decisions and effectively integrate data analytics and artificial intelligence into decision support processes. I hope this book will provide readers with more effective and data-based insights in decision-making processes.
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