[HTML][HTML] Effective RNN-based forecasting methodology design for improving short-term power load forecasts: Application to large-scale power-grid time series
AO Aseeri - Journal of Computational Science, 2023 - Elsevier
This article introduces a carefully-engineered forecasting methodology for day-ahead
electric power load forecasts evaluated using the European Network of Transmission …
electric power load forecasts evaluated using the European Network of Transmission …
Multivariate variance-based genetic ensemble learning for satellite anomaly detection
Proactive diagnosis of spacecraft issues and response to conceivable hazards has attracted
considerable interest. Hidden anomalies in satellites can cause overall system degradation …
considerable interest. Hidden anomalies in satellites can cause overall system degradation …
A deep ensemble network model for classifying and predicting breast cancer
AAV Subramanian, JP Venugopal - Computational Intelligence, 2023 - Wiley Online Library
Breast cancer is one of the leading causes of death among women worldwide. In most
cases, the misinterpretation of medical diagnosis plays a vital role in increased fatality rates …
cases, the misinterpretation of medical diagnosis plays a vital role in increased fatality rates …
[图书][B] AI in Education: Effective Machine Learning Methods To Improve Data Scarcity and Knowledge Generalization
JT Shen - 2023 - search.proquest.com
In education, machine learning (ML), especially deep learning (DL) in recent years, has
been extensively used to improve both teaching and learning. Despite the rapid …
been extensively used to improve both teaching and learning. Despite the rapid …
Deep learning algorithms for air pollution forecasting: an overview of recent developments
H Shu, Z Song, H Guo, X Chen… - … on Automation Control …, 2023 - spiedigitallibrary.org
Air pollution is a major environmental issue that affects human health and the environment.
In recent years, deep learning has been applied to the prediction of air pollution expansion …
In recent years, deep learning has been applied to the prediction of air pollution expansion …