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...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2017, 2017
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| Edition: | 1st ed. 2017 |
| Series: | Intelligent Systems Reference Library
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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.