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Inference, COmputation and Numerics for Insights into Cities (ICONIC)

洞察城市的推理、计算和数值 (ICONIC)

基本信息

批准号：
EP/P020720/2
负责人：
Mark Girolami
金额：
$ 297.36万
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FP020720%2F2
关键词：
Inference COmputation Numerics Insights into

项目摘要

There are many interesting open questions at the interface between applied mathematics, scientific computing and applied statistics.Mathematics is the language of science, we use it to describe the laws of motion that govern natural and technologicalsystems. We use statistics to make sense of data. We develop and test computer algorithms that make these ideas concrete. By bringing these concepts together in a systematic way we can validate and sharpen our hypothesis about the underlying science, and make predictions about future behaviour. This general field of Uncertainty Quantification is a very active area of research, with many challenges; from intellectual questions about how to define and measure uncertainty to very practical issues concerning the need to perform intensive computational experiments as efficiently as possible.ICONIC brings together a team of high profile researchers with the appropriate combination of skills in modeling, numerical analysis, statistics and high performance computing. To give a concrete target for impact, the ICONIC project will focus initially on Uncertainty Quantification for mathematical models relating to crime, security and resilience in urban environments. Then, acknowledging that urban analytics is a very fast-moving field where new technologies and data sources emerge rapidly, and exploiting the flexibility built into an EPSRC programme grant, we will apply the new tools to related city topics concerning human mobility, transport and infrastructure. In this way, the project will enhance the UK's research capabilities in the fast-moving and globally significant Future Cities field.The project will exploit the team's strong existing contacts with Future Cities laboratories around the world, and with nonacademic stakeholders who are keen to exploit the outcomes of the research. As new technologies emerge, and as more people around the world choose to live and work in urban environments, the Future Cities field is generating vast quantities of potentially valuable data. ICONIC will build on the UK's strength in basic mathematical sciences--the cleverness needed to add value to these data sources--in order to produce new algorithms and computational tools. The research will be conducted alongside stakeholders--including law enforcement agencies, technical IT and infrastructure providers, utility companies and policy-makers. These external partners will provide feedback and challenges, and will be ready to extract value from the tools that we develop. We also have an international Advisory Board of committed partners with relevant expertise in academic research, policymaking, law enforcement, business engagement and public outreach. With these structures in place, the research will have a direct impact on the UK economy, as the nation competes for business in the global Future Cities marketplace. Further, by focusing on crime, security and resilience we will directly improve the lives of individual citizens.

在应用数学、科学计算和应用统计学之间的界面上有许多有趣的开放问题。数学是科学的语言，我们用它来描述支配自然和技术系统的运动规律。我们使用统计数据来理解数据。我们开发和测试计算机算法，使这些想法具体化。通过以系统的方式将这些概念结合在一起，我们可以验证和强化我们关于潜在科学的假设，并对未来的行为做出预测。不确定性量化是一个非常活跃的研究领域，具有许多挑战；从如何定义和测量不确定性的智力问题到需要尽可能高效地执行密集计算实验的非常实际的问题。ICONIC汇集了一支高知名度的研究团队，他们拥有建模、数值分析、统计和高性能计算方面的适当技能组合。为了给出一个具体的影响目标，这个标志性的项目最初将专注于与城市环境中的犯罪、安全和复原力有关的数学模型的不确定性量化。然后，认识到城市分析是一个发展非常迅速的领域，新技术和数据源迅速涌现，并利用EPSRC项目拨款中内置的灵活性，我们将把新工具应用于与人类流动性、交通和基础设施相关的城市主题。通过这种方式，该项目将增强英国在快速发展和具有全球意义的未来城市领域的研究能力。该项目将利用该团队与世界各地的未来城市实验室以及热衷于利用研究成果的非学术利益相关者之间的密切联系。随着新技术的出现，以及世界各地越来越多的人选择在城市环境中生活和工作，未来城市领域正在产生大量潜在有价值的数据。为了生产新的算法和计算工具，ICONIC将建立在英国在基础数学科学方面的优势--为这些数据源增加价值所需的智慧。这项研究将与利益相关者一起进行，包括执法机构、技术信息技术和基础设施提供商、公用事业公司和政策制定者。这些外部合作伙伴将提供反馈和挑战，并准备从我们开发的工具中提取价值。我们还有一个国际咨询委员会，由在学术研究、决策、执法、商业参与和公众宣传方面具有相关专门知识的坚定合作伙伴组成。随着英国在全球未来城市市场上争夺业务，这些结构到位后，这项研究将对英国经济产生直接影响。此外，通过关注犯罪、安全和复原力，我们将直接改善公民个人的生活。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

PeriPy - A high performance OpenCL peridynamics package

PeriPy - 高性能 OpenCL 近场动力学软件包

DOI：
10.1016/j.cma.2021.114085
发表时间：
2021
期刊：
Computer Methods in Applied Mechanics and Engineering
影响因子：
7.2
作者：
Boys B
通讯作者：
Boys B

Statistical Finite Elements via Langevin Dynamics

Langevin Dynamics 的统计有限元

DOI：
10.48550/arxiv.2110.11131
发表时间：
2021
期刊：
arXiv e-prints
影响因子：
0
作者：
Akyildiz D
通讯作者：
Akyildiz D

Multilevel and Quasi Monte Carlo Methods for the Calculation of the Expected Value of Partial Perfect Information.

DOI：
10.1177/0272989x211026305
发表时间：
2022-03
期刊：
Medical decision making : an international journal of the Society for Medical Decision Making
影响因子：
0
作者：
Fang W;Wang Z;Giles MB;Jackson CH;Welton NJ;Andrieu C;Thom H
通讯作者：
Thom H

Probabilistic Integration: A Role in Statistical Computation?