Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Author: Cengiz Kahraman

Publisher: Springer

Published: 2019-07-05

Total Pages: 1392

ISBN-13: 3030237567

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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.

Intelligent Techniques for Data Science
Intelligent Techniques for Data Science

Author: Rajendra Akerkar

Publisher: Springer

Published: 2016-10-11

Total Pages: 282

ISBN-13: 3319292064

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This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p> The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Intelligent and Fuzzy Techniques: Smart and Innovative Solutions
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions

Author: Cengiz Kahraman

Publisher: Springer Nature

Published: 2020-07-10

Total Pages: 1701

ISBN-13: 3030511561

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This book gathers the most recent developments in fuzzy & intelligence systems and real complex systems presented at INFUS 2020, held in Istanbul on July 21–23, 2020. The INFUS conferences are a well-established international research forum to advance the foundations and applications of intelligent and fuzzy systems, computational intelligence, and soft computing, highlighting studies on fuzzy & intelligence systems and real complex systems at universities and international research institutions. Covering a range of topics, including the theory and applications of fuzzy set extensions such as intuitionistic fuzzy sets, hesitant fuzzy sets, spherical fuzzy sets, and fuzzy decision-making; machine learning; risk assessment; heuristics; and clustering, the book is a valuable resource for academics, M.Sc. and Ph.D. students, as well as managers and engineers in industry and the service sectors.

Fuzzy TOPSIS
Fuzzy TOPSIS

Author: Mohamed El Alaoui

Publisher: CRC Press

Published: 2021-05-26

Total Pages: 217

ISBN-13: 1000385752

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This book aims to justify the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context. It also discusses the development of the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) with related examples and MATLAB codes. This is the first book devoted to TOPSIS and its fuzzy versions. It presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making content and discusses the development of the TOPSIS method in classical and fuzzy context. The book justifies the use of fuzzy logic as an uncertainty theory and provides illustrative examples for each fuzzy TOPSIS extension, along with related MATLAB codes and case studies. This book is for industrial engineers, operations research engineers, systems engineers, and production engineers working in the areas of decision analysis, multi-criteria decision making, and multiple objective optimization.

Intelligent and Fuzzy Systems
Intelligent and Fuzzy Systems

Author: Cengiz Kahraman

Publisher: Springer Nature

Published: 2022-07-01

Total Pages: 781

ISBN-13: 3031091760

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This book presents recent research in intelligent and fuzzy techniques on digital transformation and the new normal, the state to which economies, societies, etc. settle following a crisis bringing us to a new environment. Digital transformation and the new normal-appearing in many areas such as digital economy, digital finance, digital government, digital health, and digital education are the main scope of this book. The readers can benefit from this book for preparing for a digital “new normal” and maintaining a leadership position among competitors in both manufacturing and service companies. Digitizing an industrial company is a challenging process, which involves rethinking established structures, processes, and steering mechanisms presented in this book. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying digital transformation and new normal. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

Fuzzy Computing in Data Science
Fuzzy Computing in Data Science

Author: Sachi Nandan Mohanty

Publisher: John Wiley & Sons

Published: 2022-11-03

Total Pages: 373

ISBN-13: 1394156863

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FUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation. Audience Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

Uncertainty in Computational Intelligence-Based Decision Making
Uncertainty in Computational Intelligence-Based Decision Making

Author: Ali Ahmadian

Publisher: Elsevier

Published: 2024-09-16

Total Pages: 340

ISBN-13: 044321476X

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Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others. The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science. Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision

Decision Making with Spherical Fuzzy Sets
Decision Making with Spherical Fuzzy Sets

Author: Cengiz Kahraman

Publisher: Springer Nature

Published: 2020-05-27

Total Pages: 551

ISBN-13: 3030454614

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This book introduces readers to the novel concept of spherical fuzzy sets, showing how these sets can be applied in practice to solve various decision-making problems. It also demonstrates that these sets provide a larger preference volume in 3D space for decision-makers. Written by authoritative researchers, the various chapters cover a large amount of theoretical and practical information, allowing readers to gain an extensive understanding of both the fundamentals and applications of spherical fuzzy sets in intelligent decision-making and mathematical programming.

Intelligent Systems in Digital Transformation
Intelligent Systems in Digital Transformation

Author: Cengiz Kahraman

Publisher: Springer Nature

Published: 2022-11-14

Total Pages: 626

ISBN-13: 3031165985

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This book states that intelligent digital transformation is the process of using artificial intelligence techniques in digital technologies such as machine learning, natural language processing, automation and robotics to transform existing non-digital business processes and services to meet with the evolving market and customer expectations. This book including 26 chapters, each written by their experts, focuses on revealing the reflection of digital transformation in our business and social life under emerging conditions through intelligent systems. Intelligent digital transformation examples from almost all sectors including health, education, manufacturing, tourism, insurance, smart cities, banking, energy and transportation are introduced by theory and applications. The intended readers are managers responsible for digital transformation, intelligent systems researchers, lecturers, and MSc and PhD students studying digital transformation.