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Forecasting

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Spatiotemporal neural network with attention mechanism for El Niño forecasts.

Scientific reports
To learn spatiotemporal representations and anomaly predictions from geophysical data, we propose STANet, a spatiotemporal neural network with a trainable attention mechanism, and apply it to El Niño predictions for long-lead forecasts. The STANet ma...

Establishment of Economic Forecasting Model of High-tech Industry Based on Genetic Optimization Neural Network.

Computational intelligence and neuroscience
Scientific and accurate prediction of high-tech industries is of great practical significance for government departments to grasp the future economic operation and formulate development strategies. In this paper, aiming at some shortcomings of neural...

Short-Term Demand Forecasting Method in Power Markets Based on the KSVM-TCN-GBRT.

Computational intelligence and neuroscience
With the consumption of new energy and the variability of user activity, accurate and fast demand forecasting plays a crucial role in modern power markets. This paper considers the correlation between temperature, wind speed, and real-time electricit...

A novel short-term carbon emission prediction model based on secondary decomposition method and long short-term memory network.

Environmental science and pollution research international
Grasping the dynamics of carbon emission in time plays a key role in formulating carbon emission reduction policies. In order to provide more accurate carbon emission prediction results for planners, a novel short-term carbon emission prediction mode...

Future Guidelines for Artificial Intelligence in Echocardiography.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography

Research on Impulse Power Load Forecasting Based on Improved Recurrent Neural Networks.

Computational intelligence and neuroscience
Deep learning is good at extracting the required feature quantity from the massive input information through multiple hidden layers and completing the learning through training to achieve the task of load forecasting. The impulse power load data cont...

Machine Learning, Deep Learning, and Mathematical Models to Analyze Forecasting and Epidemiology of COVID-19: A Systematic Literature Review.

International journal of environmental research and public health
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide pandemic by the World Health Organization due to its rapid spread. Since the first case was identified in Wuhan, China, the battle against this deadly disease started and ha...

Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks.

International journal of environmental research and public health
Time series data from environmental monitoring stations are often analysed with machine learning methods on an individual basis, however recent advances in the machine learning field point to the advantages of incorporating multiple related time seri...

Developed multiple-layer perceptron neural network based on developed search and rescue optimizer to predict iron ore price volatility: A case study.

ISA transactions
In economic investment, the role of forecasting is very important because in an economic project, the investor must carefully examine the dimensions of the work such that one of the most important and perhaps the main factor of a future investor and ...