Visibility graph for time series prediction and image classification: a review
The analysis of time series and images is significant across different fields due to their
widespread applications. In the past few decades, many approaches have been developed …
widespread applications. In the past few decades, many approaches have been developed …
A hybrid deep learning framework for predicting daily natural gas consumption
Conventional time-series prediction methods for natural gas consumption mainly focus on
capturing the temporal feature, neglecting static and dynamic information extraction. The …
capturing the temporal feature, neglecting static and dynamic information extraction. The …
[HTML][HTML] A stock time series forecasting approach incorporating candlestick patterns and sequence similarity
This article aims to implement trend forecasting of stock time series based on candlestick
patterns and sequence similarity. Financial time series forecasting plays a central role in …
patterns and sequence similarity. Financial time series forecasting plays a central role in …
[HTML][HTML] SimVGNets: similarity-based visibility graph networks for carbon price forecasting
In response to global warming, carbon trading market emerges to reduce carbon emissions.
However, uncertain fluctuations and complicated price mechanisms in the market have …
However, uncertain fluctuations and complicated price mechanisms in the market have …
Dynamic graph construction via motif detection for stock prediction
Stock trend prediction is crucial for recommending high-investment value stocks and can
strongly assist investors in making decisions. In recent years, the significance of stock …
strongly assist investors in making decisions. In recent years, the significance of stock …
Time-Series Forecasting Based on Fuzzy Cognitive Visibility Graph and Weighted Multisubgraph Similarity
Y Hu, F Xiao - IEEE Transactions on Fuzzy Systems, 2022 - ieeexplore.ieee.org
This article aims to address the problem of time-series forecasting. Current state-of-the-art
forecasting models lack the ability to mine the spatiotemporal dependence. How to mine …
forecasting models lack the ability to mine the spatiotemporal dependence. How to mine …
Long-term multivariate time series forecasting in data centers based on multi-factor separation evolutionary spatial–temporal graph neural networks
Data center infrastructures require constant monitoring to ensure stable and reliable
operation and time-series forecasting plays an indispensable role in intelligent operations …
operation and time-series forecasting plays an indispensable role in intelligent operations …
Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
N Giamarelos, EN Zois - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Modern power grids are faced with a series of challenges, such as the ever-increasing
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
demand for renewable energy sources, extensive urbanization, climate and energy crisis …
Deep learning with PID residual elimination network for time-series prediction of water quality in aquaculture industry
X Zhou, J Wang, Y Liu, Q Duan - Computers and Electronics in Agriculture, 2023 - Elsevier
Time-series prediction of water quality is the most critical component of water quality
monitoring in the aquaculture industry. Accurate multi-step ahead prediction of water quality …
monitoring in the aquaculture industry. Accurate multi-step ahead prediction of water quality …
Improving stock trend prediction through financial time series classification and temporal correlation analysis based on aligning change point
M Liang, X Wang, S Wu - Soft Computing, 2023 - Springer
In order to improve the accuracy of stock prediction, people major in computer science and
technology begin to apply their techniques to the financial market. In the financial market …
technology begin to apply their techniques to the financial market. In the financial market …