This repository contains the source code for the paper "A novel weighted approach for time series forecasting based on visibility graph". The method proposed in the paper leverages the characteristics of visibility graphs for time series forecasting and introduces a novel weighted approach to enhance prediction accuracy.
The project provides a Python implementation for executing the time series forecasting algorithm described in the paper. The algorithm is based on the concept of visibility graphs, constructing graphs by computing visibility between nodes, and adjusting nodes using a weighted approach to improve prediction accuracy.
We would like to thank Monash Forecasting for providing the data and code samples. You can find more resources on time series forecasting at Monash Forecasting.
@article{zhan2024novel,
title={A novel weighted approach for time series forecasting based on visibility graph},
author={Zhan, Tianxiang and Xiao, Fuyuan},
journal={Pattern Recognition},
pages={110720},
year={2024},
publisher={Elsevier}
}
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