| 书目名称 | Fuzzy Reasoning in Information, Decision and Control Systems | | 编辑 | S.G. Tzafestas,Anastasios N. Venetsanopoulos | | 视频video | | | 丛书名称 | Intelligent Systems, Control and Automation: Science and Engineering | | 图书封面 |  | | 描述 | Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is ‘fuzzy control‘, where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as ‘fuzzy expert sys tems‘, and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as ‘fuzzy information processing‘, that is to bring fuzzy idea into informa tion processing systems. | | 出版日期 | Book 1994 | | 关键词 | Processing; Software; biomedical engineering; control; fuzzy logic; information processing; logic; model; ne | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-585-34652-6 | | isbn_softcover | 978-94-017-4082-1 | | isbn_ebook | 978-0-585-34652-6Series ISSN 2213-8986 Series E-ISSN 2213-8994 | | issn_series | 2213-8986 | | copyright | Springer Science+Business Media Dordrecht 1994 |
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