Summary of Modeling Of New Energy Vehicles’ Impact on Urban Ecology Focusing on Behavior, by Run-xuan Tang
Modeling of New Energy Vehicles’ Impact on Urban Ecology Focusing on Behavior
by Run-Xuan Tang
First submitted to arxiv on: 6 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Systems and Control (eess.SY); Applications (stat.AP)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel environmental computational modeling method to assess the impact of new energy vehicles’ driving behavior on urban ecology. By analyzing behavioral patterns and usage data, specific issues like overloading batteries or driving at excessive speeds are identified as detrimental to battery performance. To simulate this interaction, an LSTM model with Bayesian optimizer is used to extend time series data from a vehicle’s life cycle to the ecological environment. The analysis reveals the negative effects of poor driving behavior on the environment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how people drive electric cars and what happens to the environment because of it. They found that some things, like not charging the car enough or driving too fast, can hurt the car’s battery and the air we breathe. To understand this better, they used a special computer model to see how all these things work together. The results show that we need to be more careful with how we drive electric cars so we don’t hurt the environment. |
Keywords
» Artificial intelligence » Lstm » Time series
