A5029780677- Soil Moisture and Remote Sensing
- Electric Vehicles and Infrastructure
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Regional Economics and Spatial Analysis
- Global Urban Networks and Dynamics
- Seismic Waves and Analysis
- Energy, Environment, and Transportation Policies
- Transportation Planning and Optimization
- Urbanization and City Planning
- 3D Surveying and Cultural Heritage
- Cultural Industries and Urban Development
- Innovation Diffusion and Forecasting
- Remote Sensing and LiDAR Applications
- Landslides and related hazards
- Railway Systems and Energy Efficiency
Chang Jung Christian University
2025
The lack of clear regulations regarding the provision electric vehicles parking lots, particularly in indoor may result inadequate fire protection and contingency planning during construction. This study investigated for vehicle lots large shopping mall, specifically scrutinizing effects charging pile locations, was conducted through field research computer simulations. Fire dynamic simulation model utilized to simulate a an lot investigate impact automatic sprinkler systems on scene....
Given the increasing environmental concerns and energy consumption, transformation of new vehicle industry is a key link in innovation structure. The shift from traditional fossil fuels to clean encompasses various dimensions such as technological innovation, policy support, infrastructure development, changes consumer preferences. Predicting future ownership electric vehicles (EVs) then estimating demand for transportation pressing issue field energy. This study starts cost, technology,...
Long-term series monitoring of ground surface settlement by remote sensing has become an effective method. Based on TS-InSAR (time Interferometric Synthetic Aperture Radar) interferometry, this paper proposes a new model based the Grey Wolf Optimizer (GWO) and Long Short-Term Memory (LSTM) to monitor predict in Kunming City. The results show that MAPE (mean absolute percentage error), RMSE (root mean square MAE error) GWO-LSTM are significantly reduced. R2 (goodness fit) six sub-study areas...