Deep analytics of non-occurring but important behaviours

对非发生但重要的行为进行深入分析

• 批准号: DP190101079
• 负责人: Prof Longbing Cao
• 金额: $ 22.49万
• 依托单位: Macquarie University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2019
• 资助国家: 澳大利亚
• 起止时间: 2019-06-04 至 2024-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP190101079
• 关键词: Deep; analytics; non; occurring; but

This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. This project expects to fill the knowledge gaps in representing, analysing and evaluating NOB complexities and impact, with significant benefits for the evidence-based detection, prediction and risk management of covert NOB applications and their important effects.

该项目旨在建立一个系统的理论，对复杂和重要的发生和未发生的行为进行深入分析。应该发生但没有发生的行为被称为不发生行为(NOB)，这种行为非常明显，但很容易被忽视，例如错过重要的医疗治疗。虽然经常发生的行为是集中的，但这种NOB可能与重大影响有关，如对健康的威胁。该项目预计将填补在表述、分析和评价国家臭氧机构复杂性和影响方面的知识空白，并对以证据为基础的国家臭氧机构应用及其重要影响的检测、预测和风险管理大有裨益。