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 Evolving Fuzzy Models. Incremental Learning, Interpretability and Stability Issues, Applications
Наименование:

Evolving Fuzzy Models. Incremental Learning, Interpretability and Stability Issues, Applications

издательство Книга по Требованию Локальные и корпоративные сети
Cтраниц 152        мягкая обложка       
Аннотация:Data-driven models possess the nice property that they can be built up generically in the sense that no underlying physical, chemical etc. laws about the system variables have to be known. This requires an adaptation of model parameters and an evolution of model structures with incremental learning steps, as a complete rebuilding from time to time with all recorded measurements would not terminate in real-time. Data driven models are mathematical models which are completely identified from data, which can be available in form of offline data sets, most commonly stored in data matrices, or in form of online measurements. Nowadays data-driven models become more and more an essential part in industrial systems for application tasks such as system identification and analysis, prediction, control or fault detection. The book addresses the on-line evolution of fuzzy models and underlines its necessity by concrete application examples from on-line quality control systems. Whenever measurements are recorded online with a certain frequency, usually the models should be kept up-to-date, especially when new system states occur during online production processes.
Издательство: Книга по Требованию
Год:2008
Цена:
2415 руб
Нет в наличии
Поиск: Evolving Fuzzy Models. Incremental Learning, Interpretability and Stability Issues, Applications
НОВЫЙ ГОД СИМВОЛ 2013 ГОДАУКРАШЕНИЯ
КАРНАВАЛ НА НОВЫЙ ГОД РАСПРОДАЖА
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