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Multi-Criteria Decision Analysis
Multi-Criteria Decision-Making (MCDM) includes methods and tools for modeling and solving complex problems. MCDM has become popular in the production and service sectors to improve the quality of service, reduce costs, and make people more prosperous. This book illustrates applications through case studies focused on disaster management. With a presentation of both Multi-Attribute Decision-Making (MADM) and Multi-Objective Decision-Making (MODM) models, this is the first book to merge these methods and tools with disaster management. This book raises awareness for society and decision-makers on how to measure readiness and what necessary preventive measures need to be taken. It offers models and case studies that can be easily adapted to solve complex problems and find solutions in other fields. Multi-Criteria Decision Analysis: Case Studies in Disaster Management will offer new insights to researchers working in the areas of industrial engineering, systems engineering, healthcare systems, operations research, mathematics, business, computer science, and disaster management, and, hopefully, the book will also stimulate further work in MCDM.
Data Science And Knowledge Engineering For Sensing Decision Support - Proceedings Of The 13th International Flins Conference
FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view.
Developments Of Artificial Intelligence Technologies In Computation And Robotics - Proceedings Of The 14th International Flins Conference (Flins 2020)
FLINS, an acronym introduced in 1994 and originally for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended into a well-established international research forum to advance the foundations and applications of computational intelligence for applied research in general and for complex engineering and decision support systems.The principal mission of FLINS is bridging the gap between machine intelligence and real complex systems via joint research between universities and international research institutions, encouraging interdisciplinary research and bringing multidiscipline researchers together.FLINS 2020 is the fourteenth in a series of conferences on computational intelligence systems.
Energy Management—Collective and Computational Intelligence with Theory and Applications
This book presents a selection of recently developed collective and computational intelligence techniques, which it subsequently applies to energy management problems ranging from performance analysis to economic analysis, and from strategic analysis to operational analysis, with didactic numerical examples. As a form of intelligence emerging from the collaboration and competition of individuals, collective and computational intelligence addresses new methodological, theoretical, and practical aspects of complex energy management problems. The book offers an excellent reference guide for practitioners, researchers, lecturers and postgraduate students pursuing research on intelligence in energy management. The contributing authors are recognized researchers in the energy research field.
Supply Chain Management Under Fuzziness
Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.
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 increasi...
Toward Humanoid Robots: The Role of Fuzzy Sets
This book offers a comprehensive reference guide for modeling humanoid robots using intelligent and fuzzy systems. It provides readers with the necessary intelligent and fuzzy tools for controlling humanoid robots by incomplete, vague, and imprecise information or insufficient data, where classical modeling approaches cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including fuzzy control, metaheuristic-based control, neutrosophic control, etc. To foster reader comprehension, all chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers, and postgraduate students pursuing research on humanoid robots. Moreover, by extending all the main aspects of humanoid robots to its intelligent and fuzzy counterparts, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas, and developments.
Solid Waste Disposal Site Selection by Using Neutrosophic Combined Compromise Solution Method
Combined Compromise Solution (COCOSO) method is a combination of di erent aggregation strategies that aim to find final scores of the alternatives with respect to determined criteria based on decision makers judgements. This method is extension of simple additive weighting and exponentially weighted product model In this paper, we extended COCOSO method to its intervalvalued neutrosophic version to increase itsapplicability to the real world problems by using the advantages of neutrosophic sets.
