Machine Learning for Intelligent Decision Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning for Intelligent Decision Science write by Jitendra Kumar Rout. This book was released on 2020-04-02. Machine Learning for Intelligent Decision Science available in PDF, EPUB and Kindle. The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.
Progress in Intelligent Decision Science
Progress in Intelligent Decision Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Progress in Intelligent Decision Science write by Tofigh Allahviranloo. This book was released on 2021-01-29. Progress in Intelligent Decision Science available in PDF, EPUB and Kindle. This book contains the topics of artificial intelligence and deep learning that do have much application in real-life problems. The concept of uncertainty has long been used in applied science, especially decision making and a logical decision must be made in the field of uncertainty or in the real-life environment that is formed and combined with vague concepts and data. The chapters of this book are connected to the new concepts and aspects of decision making with uncertainty. Besides, other chapters are involved with the concept of data mining and decision making under uncertain computations.
Applied Intelligent Decision Making in Machine Learning
Applied Intelligent Decision Making in Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Intelligent Decision Making in Machine Learning write by Himansu Das. This book was released on 2020-11-18. Applied Intelligent Decision Making in Machine Learning available in PDF, EPUB and Kindle. The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.
Deep Learning Applications and Intelligent Decision Making in Engineering
Deep Learning Applications and Intelligent Decision Making in Engineering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning Applications and Intelligent Decision Making in Engineering write by Senthilnathan, Karthikrajan. This book was released on 2020-10-23. Deep Learning Applications and Intelligent Decision Making in Engineering available in PDF, EPUB and Kindle. Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
Intelligent Decision Support Methods
Intelligent Decision Support Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Decision Support Methods write by Vasant Dhar. This book was released on 1997. Intelligent Decision Support Methods available in PDF, EPUB and Kindle. This is a comprehensive explanation of how powerful technologies work in business, using a pragmatic business approach in describing when and how they should be used. Detailed case studies are provided in management information systems, information systems, computer science, and management. The text focuses on modeling techniques such as rules, case-based reasoning, fuzzy logic, neural nets, genetic algorhithms and machine learning.
