Deep Learning for Time Series Forecasting: Tutorial and Literature Survey
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Abstract
Deep learning based forecasting methods have become the methods of choice in many applications of time series prediction or forecasting often outperforming other approaches. Consequently, over the last years, these methods are now ubiquitous in large-scale industrial forecasting applications and have consistently ranked among the best entries in forecasting competitions (e.g., M4 and M5). This practical success has further increased the academic interest to understand and improve deep forecasting methods. In this article we provide an introduction and overview of the field: We present important building blocks for deep forecasting in some depth; using these building blocks, we then survey the breadth of the…
Citation impact
297
total citations
- FWCI
- 44.43
- Percentile
- 100%
- References
- 228
Citations per year
Authors
13Topics & keywords
Topics
Keywords
- Deep learning
- Computer science
- Artificial intelligence
- Field (mathematics)
- Machine learning
- Time series
- Technology forecasting
- Scale (ratio)
UN Sustainable Development Goals
- Quality Education
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