Fuzzy Topsis

This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Engineering Education, Instructional Technology, Assessment, and E-learning. The book presents selected papers form the conference proceedings of the International Conference on Engineering Education, Instructional Technology, Assessment, and E-learning (EIAE 2006). All aspects of the conference were managed on-line.

Presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context Discusses the development of the TOPSIS method in classical and fuzzy context Justifies the use of fuzzy logic as an uncertainty theory Provides illustrative examples for each fuzzy TOPSIS extension Includes related MATLAB codes and case studies

This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.

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.

This book constitutes the refereed proceedings of the International Conference on Soft Computing in Data Science, SCDS 2017, held in Yogyakarta, Indonesia, November 27-28, 2017. The 26 revised full papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on deep learning and real-time classification; image feature classification and extraction; classification, clustering, visualization; applications of machine learning; data visualization; fuzzy logic; prediction models and e-learning; text and sentiment analytics.

The primary purpose of this book is to present the state-of-the-art of mobile cloud computing and applications with an emphasis on energy-efficiency. The future research directions are also highlighted in this book to enrich the global market-place of mobile cloud computing services facilitating the scientific, industrial, business, and consumer applications. We expect that the book will serve as a reference to a large number of readers including researchers, system architects, practitioners, and graduate-level students. This book focuses on an emerging area that has considerable research interest, momentum, and interest of commercial developers. The target reader of this book are professional developers, under-graduate and post-graduate students, and researchers. As mobile cloud computing, as well as green computing, will have a major impact on the quality of science and society over the next few years, its knowledge will enrich our readers to be at the forefront of the field. This book reports the latest research advances in the area of green mobile cloud computing. The book covers the architecture, services, methods, applications, and future research directions of green mobile cloud computing.

This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held as a hybrid event on October 29–30, 2022, in/from Istanbul Technical University. Continuing the tradition of previous volumes, it highlights recent developments of industrial engineering at the purpose of using and managing digital and intelligent technologies for application to a wide range of field, including manufacturing, healthcare, e-commerce and sustainable development. A special emphasis is given to engineering methods and strategies for managing pandemics and reducing their adverse effects on businesses.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.