AIMC Topic: Beijing

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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 Oct 18, 2022
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 ...
Neural Networks, Computer Computer Simulation Beijing Economic Development Carbon Dioxide China
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Air quality index forecast in Beijing based on CNN-LSTM multi-model.

Chemosphere Sep 1, 2022
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...
Beijing Neural Networks, Computer Forecasting Air Pollution
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Forecasting Subway Passenger Flow for Station-Level Service Supply.

Big data Jun 24, 2022
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...
Forecasting Deep Learning Neural Networks, Computer Beijing Railroads Big Data
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Robots at the Beijing 2022 Winter Olympics.

Science robotics Apr 27, 2022
The 2022 Winter Olympics has shown that robots can serve, protect, and help people excel in many aspects of their lives.
Beijing Sports Seasons Robotics Humans
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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.) Feb 15, 2022
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...
Beijing Cities Environmental Pollution China Machine Learning
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Short-Term Traffic State Prediction Based on the Critical Road Selection Optimization in Transportation Networks.

Computational intelligence and neuroscience Aug 30, 2021
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 ...
Neural Networks, Computer Transportation Beijing
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Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR.

The Science of the total environment Jul 24, 2021
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...
Beijing Neural Networks, Computer Groundwater Radar Deep Learning
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The Premium of Public Perceived Greenery: A Framework Using Multiscale GWR and Deep Learning.

International journal of environmental research and public health Jun 24, 2021
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...
Residence Characteristics Beijing Parks, Recreational Humans Deep Learning Empirical Research
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AQI time series prediction based on a hybrid data decomposition and echo state networks.

Environmental science and pollution research international May 12, 2021
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 ...
Neural Networks, Computer Forecasting Beijing Algorithms Wavelet Analysis
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Feasibility of machine learning methods for predicting hospital emergency room visits for respiratory diseases.

Environmental science and pollution research international Feb 10, 2021
The prediction of hospital emergency room visits (ERV) for respiratory diseases after the outbreak of PM is of great importance in terms of public health, medical resource allocation, and policy decision support. Recently, the machine learning method...
Beijing Machine Learning Feasibility Studies Emergency Service, Hospital Hospitals
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