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- W154300457 abstract "Many real world intelligence systems are too complex to be modeled and controled by traditional mathematical mechanism models. The large amount of data from the systems and their environment is important information which objectively and truthfully reflects the nature of complex dynamic systems. Currently the advanced digital technology has made the digitized data easy to capture and cheap to store. However, raw digital data is rarely useful in practice and the capability to extract information from raw data is extremely important for description and understanding dynamic phenomenon of the data source. The description and control of complex dynamic systems without traditional mathematical mechanism models require new methods that can utilize the existing knowledge, human experience and data. In this paper, applying Fuzzy Set logic and Fuzzy Cognitive Map (FCM), we propose an innovative data based description and control of complex dynamic systems, which is totally different from the tradition mechanism mathematical model based approaches. In the FCM framework, all necessary information for description and control of the systems is directly extracted from the raw data and human experiences. In other words, as long as a few rough simple human experiences and sufficient data are given, the proposed FCMs can describe and control a complex dynamic system for which the traditional mathematical mechanism models can not be established. As an illustrative example, the simulation results of truck back-upper control problem verify the effectiveness, validity and advantageous characteristics of the learning techniques and control ability of the proposed methodology." @default.
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- W154300457 date "2008-01-01" @default.
- W154300457 modified "2023-09-22" @default.
- W154300457 title "DYNAMIC SYSTEM DESCRIPTION AND CONTROL BASED ON DATA" @default.
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