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Graph-based deep learning for representing events at the Large Hadron Collider

Graph-based deep learning for representing events at the Large Hadron Collider
用于表示大型强子对撞机事件的基于图的深度学习
批准号:
2481007
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
Connected and autonomous vehicles have the potential to make better use of the existing road infrastructure. This project will achieve this by suggesting personalised routes to users and optimising them based on personal preferences, and creating incentive mechanisms through the use of micropayments to follow the suggested routes. We envision a system where different users have different preferences, such as travel time, congestion and price, as well as environmental factors such as pollution. In addition, mechanism design will be used to incentivise users to follow the suggested route. In particular, the project will integrate the following strands of research:1. Congestion prediction. In order to suggest a certain route, prediction of congestion is needed. In order to do so accurately, the system will use routes and destinations shared by other users of the system to predict future congestion. At the same time, the system needs to consider privacy and ensuring a privacy-by-design approach. This part of the research will build on previous work published in [1].2. Suggestion optimisation. Based on the prediction and the personal preferences of individual users, the system will come up with route suggestions that maximise "social welfare" (i.e. the total utility of everyone). The novelty here compared to existing work is that, not only time, but other dimensions such as pollution levels and availability of EV charging stations, will be considered. Hence this is a multidimensional optimisation problem.3. Micro payments for incentives. This part of the project will use game theory/mechanism design techniques to create payments that incentivise users to adhere to the recommendation. This work builds on the mechanism design applications in related work, particularly on electric vehicle charging (see [2]). The novelty here is that the payments are "ex-post", i.e. they can change on the actual conditions observed. For example, if the user was rerouted to a "better" route but it turns out to be unexpectedly congested, this would change the payment.
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海外基金
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Incentive and governance schenism study of corporate green washing behavior in China: Based on an integiated view of econfiguration of environmental authority and decoupling logic
  • 批准号:
    --
  • 项目类别:
    外国学者研究基金项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    YU BYUNGJUN
  • 依托单位:
Exploring the Intrinsic Mechanisms of CEO Turnover and Market Reaction: An Explanation Based on Information Asymmetry
  • 批准号:
    W2433169
  • 项目类别:
    外国学者研究基金项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    HAOFEI ZHANG
  • 依托单位:
含Re、Ru先进镍基单晶高温合金中TCP相成核—生长机理的原位动态研究
  • 批准号:
    52301178
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30.00万元
  • 批准年份:
    2023
  • 负责人:
    夏万顺
  • 依托单位: