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Forecasting

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Deep Data Analysis-Based Agricultural Products Management for Smart Public Healthcare.

Frontiers in public health
Agricultural is an indispensably public healthcare industry for human beings at any time and smart management of it is of great significance. Since substantial technical advance relies on long-term efforts and continuous progress, reasonably scheduli...

Forecasting carbon emissions from energy consumption in Guangdong Province, China with a novel grey multivariate model.

Environmental science and pollution research international
Carbon dioxide has a significant impact on global climate change due to its natural greenhouse effect. The objective and credible forecast of carbon emissions is very important for the government to formulate and implement the corresponding emission ...

Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources.

Sensors (Basel, Switzerland)
Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them via a late fusion based app...

A Human Resource Demand Forecasting Method Based on Improved BP Algorithm.

Computational intelligence and neuroscience
Human resources are the first resource for enterprise development, and a reasonable human resource structure will increase the effectiveness of an enterprise's human resource input and output. The reality is that even if an enterprise designs a human...

Machine learning in medical applications: A review of state-of-the-art methods.

Computers in biology and medicine
Applications of machine learning (ML) methods have been used extensively to solve various complex challenges in recent years in various application areas, such as medical, financial, environmental, marketing, security, and industrial applications. ML...

China's Economic Forecast Based on Machine Learning and Quantitative Easing.

Computational intelligence and neuroscience
In this paper, six variables, including export value, real exchange rate, Chinese GDP, and US IPI, and their seasonal variables, are used as determinants to model and forecast China's export value to the US using three methods: BP neural network, ARI...

Generative adversarial networks for biomedical time series forecasting and imputation.

Journal of biomedical informatics
In the present systematic review we identified and summarised current research activities in the field of time series forecasting and imputation with the help of generative adversarial networks (GANs). We differentiate between imputation which descri...

New double decomposition deep learning methods for river water level forecasting.

The Science of the total environment
Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the practical and sustainable use of available water resources. We propose a new deep learning hybrid model for SWL forecasting using convolutional neural networks...

Research and Forecast Analysis of Financial Stability for Policy Uncertainty.

Computational intelligence and neuroscience
The instability of financial market will have a great impact on money, bonds, and stocks and affect the economic development of society and people's lives. Therefore, it is very necessary for us to study and predict the financial stability. According...