Time-Series Prediction and Applications A Machine Intelligence Approach /

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 g...

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Detaylı Bibliyografya
Asıl Yazarlar: Konar, Amit (Yazar), Bhattacharya, Diptendu (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edisyon:1st ed. 2017.
Seri Bilgileri:Intelligent Systems Reference Library, 127
Konular:
Computational intelligence.
Artificial intelligence.
Mathematics > Data processing.
Computational Intelligence.
Artificial Intelligence.
Computational Mathematics and Numerical Analysis.
Online Erişim:Full-text access
OPAC'ta görüntüle
İçindekiler:
  • An Introduction to Time-Series Prediction
  • Prediction Using Self-Adaptive Interval Type-2 Fuzzy Sets
  • Handling Multiple Factors in the Antecedent of Type-2 Fuzzy Rules
  • Learning Structures in an Economic Time-Series for Forecasting Applications
  • Grouping of First-Order Transition Rules for Time-Series Prediction by Fuzzy-induced Neural Regression
  • Conclusions and Future Directions. .

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