Transductive LSTM for time-series prediction: An application to weather forecasting-Reference-Cited by-同舟云学术

Transductive LSTM for time-series prediction: An application to weather forecasting

Published:2020-05 Issue: Volume:125 Page:1-9
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Karevan Zahra,Suykens Johan A.K.^ORCID

Funder

Research Council KUL, Belgium

PhD/Postdoc grants Flemish Government

FWO, Belgium

ERC Advanced Grant E-DUALITY

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference31 articles.

1. Forecasting across time series databases using long short-term memory networks on groups of similar series;Bandara,2017

2. The quiet revolution of numerical weather prediction;Bauer;Nature,2015

3. Learning long-term dependencies with gradient descent is difficult;Bengio;IEEE Transactions on Neural Networks,1994

4. Local learning algorithms;Bottou;Neural Computation,1992

5. Three-layer weighted fuzzy support vector regression for emotional intention understanding in human-robot interaction;Chen;IEEE Transactions on Fuzzy Systems,2018

Cited by 304 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. TFformer: A time–frequency domain bidirectional sequence-level attention based transformer for interpretable long-term sequence forecasting;Pattern Recognition;2025-02

2. A hybridized LSTM-ANN-RSA based deep learning models for prediction of COVID-19 cases in Eastern European countries;Expert Systems with Applications;2024-12

3. Machine Learning for public transportation demand prediction: A Systematic Literature Review;Engineering Applications of Artificial Intelligence;2024-11

4. A study on the prediction of service reliability of wireless telecommunication system via distribution regression;Reliability Engineering & System Safety;2024-10

5. Evaluation and Prediction of Climatic parameters based on IoT system using Machine learning and Neural network algorithms;2024-09-11