Explainable machine learning for electrification of everything

可解释的机器学习，实现万物电气化

• 批准号: LP230100439
• 负责人: Prof Mahdi Jalili
• 金额: $ 34.81万
• 依托单位: RMIT University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP230100439
• 关键词: Explainable; machine; learning; electrification; everything; Explainable; machine; learning; electrification; everything

The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of this project includes a data-informed decision support technology to help consumers choose the best electrification technologies and solutions. This should provide significant benefits, such as increasing community engagement with electrification, and thus reducing their carbon footprint.

能源部门是温室气体排放的最大贡献者。 “所有事物电气化”与可再生能源的发电相结合是脱碳和运输扇区的关键解决方案。该项目旨在开发可解释的基于机器学习的技术驱动技术，以准确预测电气化对消费者能耗和成本的影响。该项目的预期结果包括一项数据知识的决策支持技术，以帮助消费者选择最佳的电气化技术和解决方案。这应该提供重大的好处，例如增加社区与电气化的参与，从而减少其碳足迹。