An investigation into the application of machine learning algorithms for the discrimination, classification and optimal application of a military (nuc

机器学习算法在军队识别、分类和优化应用中的应用研究（nuc

• 批准号: 2750505
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2750505
• 关键词: investigation; into; application; machine; learning

The proposal is to investigate how machine learning techniques can be used as part of a nuclear missile defence system. Combining the knowledge of the candidate employer AWE, the organisation responsible for the U.K.'s nuclear weapons programme, with defence and machine learning experts in academia. This will differ from pre-existing research due to the involvement and response to nuclear weapon effects, an area of specific interest to AWE. The objectives of the project can be summarised as follows. Firstly, to investigate machine learning algorithms that can correctly discriminate and classify threats and nuclear devices, then respond to the scenario detected with optimal usage of its assets, while operating around nuclear environments. Secondly, develop the candidate's skillset in machine learning techniques to then be able to apply them to additional future areas of work. Finally, to train the candidate to a competent level of expertise in many of the required fields (such as radar systems). The outcomes are expected to be the relevant high standard documentation of findings, representative computational models and subject matter expertise to the candidate.

该提案旨在研究如何将机器学习技术用作核导弹防御系统的一部分。将候选雇主 AWE（负责英国核武器计划的组织）的知识与学术界的国防和机器学习专家相结合。由于涉及和响应核武器效应，这将不同于现有的研究，这是 AWE 特别感兴趣的领域。该项目的目标可概括如下。首先，研究能够正确区分和分类威胁和核装置的机器学习算法，然后在核环境周围运行时，以最佳方式利用其资产来响应检测到的场景。其次，培养候选人在机器学习技术方面的技能，以便能够将其应用到未来的其他工作领域。最后，培训候选人在许多所需领域（例如雷达系统）达到合格的专业水平。预计结果将为候选人提供相关的高标准研究结果文件、代表性计算模型和主题专业知识。