Emerging Technologies and Dynamic Decision MakingКНИГИ » ОС И БД
Название: Emerging Technologies and Dynamic Decision Making Автор: Hassan Qudrat-Ullah Издательство: World Scientific Publishing Серия: Systems Thinking and Dynamic Decision Making: Volume 1 Год: 2026 Страниц: 661 Язык: английский Формат: pdf (true) Размер: 10.1 MB
Emerging Technologies and Dynamic Decision Making delves into the transformative role of cutting-edge technologies — such as Artificial Intelligence (AI), blockchain, IoT, and Quantum Computing — on decision-making processes in complex, fast-paced environments. The book is structured into four parts, beginning with an introduction to these technologies and the dynamic decision-making frameworks required to manage the inherent uncertainties they bring. It explores how these innovations disrupt traditional models across industries, reshaping everything from socioeconomic systems to governance structures.
The book addresses the interplay between technology and decision-making, providing detailed case studies from sectors like healthcare, finance, and emergency management. It highlights the societal and ethical challenges posed by rapid technological integration, such as issues of equity, transparency, and privacy. Additionally, it offers a dynamic perspective on decision-support systems, Big Data, and real-time analytics, showing how organizations can leverage these advancements to enhance strategic outcomes.
Practical insights are provided through a focus on adaptive and agile decision-making models, which enable organizations to thrive amidst technological disruption. The book concludes with strategic foresight, encouraging readers to anticipate future trends and prepare for the ethical, societal, and economic challenges that emerging technologies will continue to introduce.
AI and ML technologies are transforming the decision-making landscape by providing real-time, data-driven insights that enhance responsiveness and agility. These technologies enable organizations to analyze vast datasets, recognize patterns, and generate actionable insights almost instantaneously, reshaping how decisions are made across various industries. AI and ML are pivotal in real-time decision-making, thanks to their ability to process and analyze large datasets with speed and precision. Algorithms such as neural networks, decision trees, and clustering models allow systems to learn from data and adapt to changing conditions dynamically. This capability is crucial for businesses operating in fast-paced environments, where traditional decision-making methods may fail to keep up.
This book is a comprehensive guide for professionals, researchers, and decision-makers seeking to navigate the intersection of emerging technologies and dynamic decision-making frameworks.
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