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Application of hybrid fuzzy interval-based machine learning models on financial time series — A case study of Taiwan biotech index during the epidemic period
Frontiers
In recent years, the use of machine learning to predict stock market indices has emerged as a vital concern in the FinTech domain.
1 week ago
A novel extreme adaptive GRU for multivariate time series forecasting
Nature
Multivariate time series forecasting is a critical problem in many real-world scenarios. Recent advances in deep learning have significantly...
5 months ago
Histogram errors plot for the proposed system in predicting cellular...
ResearchGate
Download scientific diagram | Histogram errors plot for the proposed system in predicting cellular loading traffic at the training phase: (a) January 2018,...
3 days ago
New survey on deep learning solutions for cellular traffic prediction
Tech Xplore
The bustling streets of a modern city are filled with countless individuals using their smartphones for streaming videos, sending messages...
3 months ago
Temporal Graph Learning in 2024. Continue the journey for evolving… | by Shenyang(Andy) Huang
Towards Data Science
Many complex networks evolve over time including transaction networks, traffic networks, social networks and more. Temporal Graph Learning...
5 months ago
Advancing diabetes prediction with a progressive self-transfer learning framework for discrete time series data
Nature
Although diabetes mellitus is a complex and pervasive disease, most studies to date have focused on individual features,...
7 months ago
Precipitation forecasting: from geophysical aspects to machine learning applications
Frontiers
Intense precipitation events pose a significant threat to human life. Mathematical and computational models have been developed to simulate atmospheric...
2 weeks ago
GREEN.DAT.AI: Enabling energy-efficient AI services
Innovation News Network
GREEN.DAT.AI is accelerating the green energy transition through the development of energy-efficient AI services and data spaces.
8 months ago
Interpretable Deep Learning for Time Series Forecasting
Google Research
Posted by Sercan O. Arik, Research Scientist and Tomas Pfister, Engineering Manager, Google Cloud Multi-horizon forecasting, i.e. predicting...
30 months ago
Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models
BMC Public Health
Mathematical and statistical models are used to predict trends in epidemic spread and determine the effectiveness of control measures.
11 months ago