Strategic Fuzzy Extensions And Decision Making Techniques
Download Strategic Fuzzy Extensions And Decision Making Techniques PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Strategic Fuzzy Extensions And Decision Making Techniques book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Strategic Fuzzy Extensions and Decision-making Techniques
The application of a novel correlation coefficient of linguistic intuitionistic fuzzy sets to medical diagnosis problems provides the topic for Strategic Fuzzy Extensions and Decision-making Techniques. It further explains neutrosophic cubic set-based aggregation operators for library ranking systems, and techniques for order performance by similarity to ideal solution. The text also introduces the new aggregation operators, similarity measures, and distance measures for the fuzzy sets and their extensions. This book: Introduces the new aggregation operators, similarity measures, and distance measures for the fuzzy sets and their extensions. Covers recent studies in the field of fuzzy optimization and decision making such as advanced decision-making algorithms. Highlights the application in the field of image processing and pattern recognition. Presents a technique for order performance by similarity to an ideal solution and VIKOR method for decision-making. Explores the limitations of existing fuzzy decision-making approaches such as the malfunctioning of existing formulations. It is primarily written for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, manufacturing engineering, production engineering, mechanical engineering, and engineering mathematics.
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making
This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.
Analytic Hierarchy Process with Fuzzy Sets Extensions
This book presents a comprehensive guide to Analytic Hierarchy Process with Fuzzy Sets Extensions. Written by prominent researchers, it offers readers a step-by-step approach to decision-making that can be applied to a wide range of real-world problems. With clear explanations and practical examples, this book is an essential resource for researchers, lecturers, and postgraduate students pursuing research on Analytic Hierarchy Process with Fuzzy Sets Extensions. Each chapter in the book provides a wealth of both basic and advanced concepts, including Interval Type-2 Fuzzy AHP, Intuitionistic Fuzzy AHP, Hesitant Fuzzy AHP, Pythagorean Fuzzy AHP, Picture Fuzzy AHP, q-Rung Orthopair Fuzzy AHP, Spherical Fuzzy AHP, Circular Intuitionistic Fuzzy AHP, and Decomposed Fuzzy AHP. To foster a better understanding, all the chapters include relevant numerical examples or case studies, making it easy to apply the concepts in practice. Moreover, the book extends all the main aspects of Analytic Hierarchy Process with Fuzzy Sets Extensions, presenting a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments. In summary, this book is an essential reference guide for anyone seeking to gain a deep understanding of Analytic Hierarchy Process with Fuzzy Sets Extensions. It is written in a rigorous and scholarly manner, making it a valuable resource for researchers and academics. Order your copy today and discover the practical insights and strategies for decision-making offered by this authoritative volume.