Fuzzy Systems And Data Mining Iv


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Fuzzy Systems and Data Mining IV


Fuzzy Systems and Data Mining IV

Author: A.J. Tallón-Ballesteros

language: en

Publisher: IOS Press

Release Date: 2018-11-06


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Big Data Analytics is on the rise in the last years of the current decade. Data are overwhelming the computation capacity of high performance servers. Cloud, grid, edge and fog computing are a few examples of the current hype. Computational Intelligence offers two faces to deal with the development of models: on the one hand, the crisp approach, which considers for every variable an exact value and, on the other hand, the fuzzy focus, which copes with values between two boundaries. This book presents 114 papers from the 4th International Conference on Fuzzy Systems and Data Mining (FSDM 2018), held in Bangkok, Thailand, from 16 to 19 November 2018. All papers were carefully reviewed by program committee members, who took into consideration the breadth and depth of the research topics that fall within the scope of FSDM. The acceptance rate was 32.85% . Offering a state-of-the-art overview of fuzzy systems and data mining, the publication will be of interest to all those whose work involves data science.

Fuzzy Systems and Data Mining V


Fuzzy Systems and Data Mining V

Author: A.J. Tallón-Ballesteros

language: en

Publisher: IOS Press

Release Date: 2019-11-06


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The Fuzzy Systems and Data Mining (FSDM) conference is an annual event encompassing four main themes: fuzzy theory, algorithms and systems, which includes topics like stability, foundations and control; fuzzy application, which covers different kinds of processing as well as hardware and architectures for big data and time series and has wide applicability; the interdisciplinary field of fuzzy logic and data mining, encompassing applications in electrical, industrial, chemical and engineering fields as well as management and environmental issues; and data mining, outlining new approaches to big data, massive data, scalable, parallel and distributed algorithms. The annual conference provides a platform for knowledge exchange between international experts, researchers, academics and delegates from industry. This book includes the papers accepted and presented at the 5th International Conference on Fuzzy Systems and Data Mining (FSDM 2019), held in Kitakyushu, Japan on 18-21 October 2019. This year, FSDM received 442 submissions. All papers were carefully reviewed by program committee members, taking account of the quality, novelty, soundness, breadth and depth of the research topics falling within the scope of FSDM. The committee finally decided to accept 137 papers, which represents an acceptance rate of about 30%. The papers presented here are arranged in two sections: Fuzzy Sets and Data Mining, and Communications and Networks. Providing an overview of the most recent scientific and technological advances in the fields of fuzzy systems and data mining, the book will be of interest to all those working in these fields.

Fuzzy System and Data Mining


Fuzzy System and Data Mining

Author: G. Chen

language: en

Publisher: IOS Press

Release Date: 2016-04-14


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Fuzzy logic is widely used in machine control. The term ‘fuzzy’ refers to the fact that the logic involved can deal with concepts that cannot be expressed as either ‘true’ or ‘false’, but rather as ‘partially true’. Fuzzy set theory is very suitable for modeling the uncertain duration in process simulation, as well as defining the fuzzy goals and fuzzy constraints of decision-making. It has many applications in industry, engineering and social sciences. This book presents the proceedings of the 2015 International Conference on Fuzzy Systems and Data Mining (FSDM2015), held in Shanghai, China, in December 2015. The application domain covers geography, biology, economics, medicine, the energy industry, social science, logistics, transport, industrial and production engineering, and computer science. The papers presented at the conference focus on topics such as system diagnosis, rule induction, process simulation/control, and decision-making. They include papers on solving practical problems with intelligent algorithms; statistical analysis; classification and clustering; and association rule learning. They also reflect the frontier in data mining research and address the challenges posed to data analytics research by the increasingly large datasets yielded by many application domains, together with new types of unstructured data. The book provides an overview of the ways in which fuzzy theory and data mining principles are applied in various fields, and will be of interest to all those who work in either the theory or practice of fuzzy systems and data mining.