A Novel Discrete Time Series Representation With De Bruijn Graphs for Enhanced Forecasting Using TimesNet

A Novel Discrete Time Series Representation With De Bruijn Graphs for Enhanced Forecasting Using TimesNet

<p dir="ltr">In this paper, we present a novel method for advancing time series forecasting by representing discretized time series data through de Bruijn Graphs (dBGs). This method harnesses the capability of dBGs to encapsulate and project future states from historical sequences, t...

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Bibliographic Details
Main Author: Mert Onur Cakiroglu (22927777) (author)
Other Authors: Hasan Kurban (13144983) (author), Elham Buxton (22927780) (author), Mehmet Dalkilic (13144986) (author)
Published: 2025
Subjects:
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Machine learning
Time series analysis
De Bruijn graph
TimesNet
graph embeddings
Forecasting
Feature extraction
Predictive models
Data models
Transformers
Encoding
Computational modeling
Accuracy
Training
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