Page 840 - AI for Good Innovate for Impact
P. 840

AI for Good Innovate for Impact



                      [7]  Yong, P., et al. "Evaluating the Dispatchable Capacity of Base Station Backup Batteries
                           in Distribution Networks." IEEE Transactions on Smart Grid 12, no. 5 (September 2021):
                           3966–3979. https:// doi .org/ 10 .1109/ TSG .2021 .307475.
                      [8]  National Renewable Energy Laboratory (NREL).  EV Battery Consumption Charging
                           Patterns. Accessed June 19, 2025. https:// www .nrel .gov/ docs/ fy24osti/ 85902 .pdf.
                      [9]  Google Earth Engine. Elevation, Congestion, Road Condition Datasets. Accessed June
                           19, 2025. https:// developers .google .com/ earth -engine/ datasets.
                      [10]  NASA POWER. Temperature and Humidity Data Access Viewer. Accessed June 19, 2025.
                           https:// power .larc .nasa .gov/ data -access -viewer/ .
                      [11]  Bureau of Energy Efficiency (India). Energy Consumption Benchmark Reports. Accessed
                           June 19, 2025. https:// beeindia .gov .in/ en/ publications #id -reports -studies.
                      [12]  GitHub. Chronos Forecasting RMSE: 0.001443. Accessed June 19, 2025. https:// github
                           .com/ .
                      [13]  FG Research. Chronos Forecasting MAE: 0.001105. Accessed June 19, 2025.
                      [14]  arXiv. Chronos Accuracy Metrics (RMSE, MAE). Accessed June 19, 2025. https:// arxiv .org/
                           .
                      [15]  OpenTopography. Sequential Flow Input: Start and End GPS Coordinates. Accessed June
                           19, 2025. https:// opentopography .org/ .
                      [16]  arXiv. Hierarchical Architecture: Middle Layer–Predictive Modelling. Accessed June 19,
                           2025. https:// arxiv .org/ .
                      [17]  OpenTopography. Terrain-Aware Processing Data Sources. Accessed June 19, 2025.
                           https:// opentopography .org/ .
                      [18]  Mistral Solutions. Deployment Platforms: NVIDIA Jetson Nano and Xavier. Accessed June
                           19, 2025.
                      [19]  Mistral Solutions. Tensor LLTM Performance Optimization. Accessed June 19, 2025.
                           https:// github .com/ .
                      [20]  Mistral Solutions. Edge Device Performance Metrics: Latency and Power Consumption.
                           Accessed June 19, 2025. https:// developer .nvidia .com/ .
                      [21]  FG Research. Chronos Evaluation Metrics: RMSE and MAE. Accessed June 19, 2025.
                      [22]  Mistral Solutions. Mistral Evaluation Metrics: Latency. Accessed June 19, 2025. https://
                           developer .nvidia .com/ .
                      [23]  NVIDIA. Deep Reinforcement Learning in Robotics with Jetson: Reward Convergence.
                           Accessed June 19, 2025.
                      [24]  FG Research. Driver-Specific Variations in Chronos Forecasting. Accessed June 19, 2025.
































                  804
   835   836   837   838   839   840   841   842   843   844   845