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The energy consumption of the HVAC system accounts for a significant portion of the energy consumption of the public building system, and using an efficient energy consumption prediction model can assist it in carrying out effective energy-saving transformation. Unlike the traditional energy consumption prediction model, this paper extracts features from large data sets using XGBoost, trains them separately to obtain multiple models, then fuses them with LightGBMs independent prediction results using MAE, infers energy consumption related variables, and successfully applies this model to the self-developed Internet of Things platform.
Lane-changing is an important driving behavior and unreasonable lane changes can result in potentially dangerous traffic collisions. Advanced Driver Assistance System (ADAS) can assist drivers to change lanes safely and efficiently. To capture the st
To accommodate the unprecedented increase of commercial airlines over the next ten years, the Next Generation Air Transportation System (NextGen) has been implemented in the USA that records large-scale Air Traffic Management (ATM) data to make air t
Power management is an expensive and important issue for large computational infrastructures such as datacenters, large clusters, and computational grids. However, measuring energy consumption of scalable systems may be impractical due to both cost a
We use grey forecast model to predict the future energy consumption of four states in the U.S, and make some improvments to the model.
In 2020, the COVID-19 pandemic spreads all over the world. In order to alleviate the spread of the epidemic, various blockade policies have been implemented in many areas. In order to formulate a better epidemic prevention policy for urban energy con