Hesitant Fuzzy Set

Hesitant Fuzzy Set
Author: Bahram Farhadinia
Publisher: Springer Nature
Total Pages: 162
Release: 2021-12-04
Genre: Computers
ISBN: 9811673012

Covering a wide range of notions concerning hesitant fuzzy set and its extensions, this book provides a comprehensive reference to the topic. In the case where different sources of vagueness appear simultaneously, the concept of fuzzy set is not able to properly model the uncertainty, imprecise and vague information. In order to overcome such a limitation, different types of fuzzy extension have been introduced so far. Among them, hesitant fuzzy set was first introduced in 2010, and the existing extensions of hesitant fuzzy set have been encountering an increasing interest and attracting more and more attentions up to now. It is not an exaggeration to say that the recent decade has seen the blossoming of a larger set of techniques and theoretical outcomes for hesitant fuzzy set together with its extensions as well as applications.As the research has moved beyond its infancy, and now it is entering a maturing phase with increased numbers and types of extensions, this book aims to give a comprehensive review of such researches. Presenting the review of many and important types of hesitant fuzzy extensions, and including references to a large number of related publications, this book will serve as a useful reference book for researchers in this field.

Multiple Criteria Decision Making Methods with Multi-polar Fuzzy Information

Multiple Criteria Decision Making Methods with Multi-polar Fuzzy Information
Author: Muhammad Akram
Publisher: Springer Nature
Total Pages: 564
Release: 2024-01-04
Genre: Technology & Engineering
ISBN: 3031436369

This book presents an extension of fuzzy set theory allowing for multi-polar information, discussing its impact on the theoretical and practical development of multi-criteria decision making. It reports on set of hybrid models developed by the authors, and show how they can be adapted, case by case, to the lack of certainty under a variety of criteria. Among them, hybrid models combining m-polar fuzzy sets with rough, soft and 2-tuple linguistic sets, and m-polar hesitant fuzzy sets and hesitant m-polar fuzzy are presented, together with some significant applications. In turn, outranking decision-making techniques such as m-polar fuzzy ELECTRE I, II, III and IV methods, as well as m-polar fuzzy PROMETHEE I and II methods, are developed. The efficiency of these decision-making procedures, as well as other possible extensions studied by the authors, is shown in some real-world applications. Overall, this book offers a guide on methodologies to deal with the multi-polarity and fuzziness of the real-world problems, simultaneously. By including algorithms and computer programming codes, it provides a practice-oriented reference guide to both researchers and professionals working at the interface between computational intelligence and decision making.

Fuzzy Decision-Making Methods Based on Prospect Theory and Its Application in Venture Capital

Fuzzy Decision-Making Methods Based on Prospect Theory and Its Application in Venture Capital
Author: Xiaoli Tian
Publisher: Springer Nature
Total Pages: 161
Release: 2021-03-22
Genre: Business & Economics
ISBN: 9811602433

This book gives a thorough and systematic introduction to the latest research results about fuzzy decision-making method based on prospect theory. It includes eight chapters: Introduction, Intuitionistic fuzzy MADM based on prospect theory, QUALIFLEX based on prospect theory with probabilistic linguistic information, Group PROMETHEE based on prospect theory with hesitant fuzzy linguistic information, Prospect consensus with probabilistic hesitant fuzzy preference information, Improved TODIM based on prospect theory and the improved TODIM with probabilistic hesitant fuzzy information, etc. This book is suitable for the researchers in the fields of fuzzy mathematics, operations research, behavioral science, management science and engineering, etc. It is also useful as a textbook for postgraduate and senior-year undergraduate students of the relevant professional institutions of higher learning.

Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications

Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications
Author: Chenyang Song
Publisher: Springer Nature
Total Pages: 186
Release: 2021-10-03
Genre: Business & Economics
ISBN: 9811658005

This book mainly introduces some techniques of decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment and expands the applications of hesitant fuzzy sets in solving practical problems. The book pursues three major objectives: (1) to introduce some techniques about decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment, (2) to prove these techniques theoretically and (3) to apply the involved techniques to practical problems. The book is especially valuable for readers to understand how hesitant fuzzy set could be employed in decision-making, uncertain reasoning and regression analysis and motivates researchers to expand more application fields of hesitant fuzzy set.

Fuzzy Techniques for Decision Making 2018

Fuzzy Techniques for Decision Making 2018
Author: José Carlos R. Alcantud
Publisher: MDPI
Total Pages: 776
Release: 2020-12-02
Genre: Technology & Engineering
ISBN: 3039364154

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches.

Computational Intelligence

Computational Intelligence
Author: Dinesh C.S. Bisht
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 224
Release: 2020-08-10
Genre: Technology & Engineering
ISBN: 3110668335

Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.

Large-Scale Group Decision-Making

Large-Scale Group Decision-Making
Author: Su-Min Yu
Publisher: Springer Nature
Total Pages: 195
Release: 2022-01-03
Genre: Business & Economics
ISBN: 9811678898

This book explores clustering operations in the context of social networks and consensus-reaching paths that take into account non-cooperative behaviors. This book focuses on the two key issues in large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimension of a large group. Consensus reaching requires that the divergent individual opinions of the decision makers converge to the group opinion. This book emphasizes the similarity of opinions and social relationships as important measurement attributes of clustering, which makes it different from traditional clustering methods with single attribute to divide the original large group without requiring a combination of the above two attributes. The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters’ opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers. Graduates and researchers in the fields of management science, computer science, information management, engineering technology, etc., who are interested in large-scale group decision-making and consensus building are potential audience of this book. It helps readers to have a deeper and more comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making.

Big Data Quantification for Complex Decision-Making

Big Data Quantification for Complex Decision-Making
Author: Zhang, Chao
Publisher: IGI Global
Total Pages: 328
Release: 2024-04-16
Genre: Business & Economics
ISBN:

Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making. The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains.

Decision Support Systems for Sustainable Computing

Decision Support Systems for Sustainable Computing
Author: Muhammet Deveci
Publisher: Elsevier
Total Pages: 286
Release: 2024-05-23
Genre: Computers
ISBN: 0443235988

Decision Support Systems for Sustainable Computing investigates recent technological advances in decision support systems models designed to solve real world applications. The book provides a broad overview of digital technology transformation as applied to the circular economy which is seeking to drive improvements in scientific research, communication, logistics, automation, production, and the improved sustainability of these processes and products. The book explores applications of decision support for sustainable development across supply chain management, business intelligence, agriculture, aviation, communications, and finance. - Provides a broad overview of emerging trends and technologies in decision support systems applications - Investigates recent trends and core concepts in digital technology transformation as applied to the circular economy and sustainable development - Analyzes the application of decision support systems models across a range of case studies and processes which rely on multi-criteria decision-making and have been designed specifically to improve overall sustainability