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Short-Term Traffic State Prediction Based on the Critical Road Selection Optimization in Transportation Networks.

Computational intelligence and neuroscience
Short-term traffic prediction under corrupted or missing data for large-scale transportation networks has become an important and challenging topic in recent decades. Since the critical roads have predictive power on their adjacent roads, this paper ...

AQI time series prediction based on a hybrid data decomposition and echo state networks.

Environmental science and pollution research international
A hybrid AQI time series prediction model is proposed based on EWT-SE-VMD secondary decomposition, ICA (imperialist competitive algorithm) feature selection, and ESN (echo state network) neural network. Firstly, EWT (empirical wavelet transform) and ...

The Premium of Public Perceived Greenery: A Framework Using Multiscale GWR and Deep Learning.

International journal of environmental research and public health
Population agglomeration and real estate development encroach on public green spaces, threatening human settlement equity and perceptual experience. Perceived greenery is a vital interface for residents to interact with the urban eco-environment. Nev...

Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR.

The Science of the total environment
The demand for water resources during urbanization forces the continuous exploitation of groundwater, resulting in dramatic piezometric drawdown and inducing regional land subsidence (LS). This has greatly threatened sustainable development in the lo...

Spatial distribution and influencing factors of litter in urban areas based on machine learning - A case study of Beijing.

Waste management (New York, N.Y.)
Littering in urban areas negatively affects their appearance, is harmful to the environment and increases pollution. It is a typical urban problem looming large upon Beijing and other megacities striving for liveability and harmony in economy, societ...

Robots at the Beijing 2022 Winter Olympics.

Science robotics
The 2022 Winter Olympics has shown that robots can serve, protect, and help people excel in many aspects of their lives.

Forecasting Subway Passenger Flow for Station-Level Service Supply.

Big data
Demand forecasting is one of the managers' concerns in service supply chain management. With accurate passenger flow forecasting, the station-level service suppliers can make better service plans accordingly. However, the existing forecasting model c...

Air quality index forecast in Beijing based on CNN-LSTM multi-model.

Chemosphere
Accurate predicting the air quality trend can provide a theoretical basis for environmental protection management and decision-making. This study proposed the convolutional neural networks-long short-term memory (CNN-LSTM) model, which was proposed t...

A novel grey prediction model with a feedforward neural network based on a carbon emission dynamic evolution system and its application.

Environmental science and pollution research international
The objective and accurate prediction of carbon dioxide emissions holds great significance for improving governmental energy policies and plans. Therefore, starting from an evolutionary system of carbon emissions, this paper studies the evolution of ...

Beijing's central role in global artificial intelligence research.

Scientific reports
Nations worldwide are mobilizing to harness the power of Artificial Intelligence (AI) given its massive potential to shape global competitiveness over the coming decades. Using a dataset of 2.2 million AI papers, we study inter-city citations, collab...