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Название: Time-Series Prediction and Applications: A Machine Intelligence Approach
Автор: Amit Konar, Diptendu Bhattacharya
Издательство: Springer
Год: 2017
Страниц: 242
Формат: PDF
Размер: 10 Mb
Язык: English
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series