ST-GMLP: A concise spatial-temporal framework based on gated multi-layer perceptron for traffic flow forecasting.

The field of traffic forecasting has been the subject of considerable attention as a critical component in alleviating traffic congestion and improving urban services. Given the regular patterns of human activities, it is evident that traffic flow is inherently periodic. However, most of existing studies restrict themselves to recent historical observations and typically yield structurally and computationally complex models, which greatly limits the forecasting accuracy and hinders the application of models in realistic situations.

Forecast of passenger car market structure and environmental impact analysis in China.

To evaluate the future passenger car market related environmental impact, first, a competitive prediction model was introduced based on Lotka-Volterra model. Further, the limit of passenger car life cycle system is extended to analyze the scale of future energy consumption and pollutant emission. The proportion of new energy passenger cars, average rate of change in the quality of passenger cars, and the share of renewable energy power generation were used as evaluation indicators to conduct scenario simulations for assessing the environmental benefits under the following policy scenarios: lightweight, electrification, and end-use energy cleaning of automobile.