Artificial Intelligence meets Multi-Criteria Decision Aiding in smart sustainble cities

人工智能在可持续智慧城市中满足多标准决策辅助

• 批准号: RGPIN-2020-05642
• 负责人: AbiZeid, Irène
• 金额: $ 1.89万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=740700
• 关键词: Artificial; Intelligence; meets; Multi; Criteria

In today's organizations, transparency and accountability are increasingly required, especially for decisions involving environmental and public resources, which have an impact on groups with diverse vulnerability levels and conflicting interests. This is particularly true when it comes to city planning and management where issues with drinking water source protection, wastewater management, transportation planning, social housing planning or street rehabilitation must be addressed in a context of increasing awareness of social inequities and environmental degradation related to anthropogenic activities, and in an era of social media, citizens participation and big data. This context has led, in the mid 2010s, to the emergence of the concept of smart sustainable cities, i.e. cities which, "supported by information and communications technologies (ICT) and aware of local or environmental limitations, meet the needs of their current inhabitants without compromising the ability of other people or other generations to meet their needs" (Höjer & Wangel, 2015). But how can a city evolve toward a smart sustainable city? How can public decision processes be conducted to ensure sustainable, robust, rigorous, inclusive, transparent, acceptable and fair decisions while taking advantage of the ICT infrastructure? The answer is interdisciplinary and lies partly in the field of Analytics, more precisely in participatory multicriteria decision aiding (MCDA), a sub-discipline of operations research, which has gained an increasing momentum over the last five decades, and in its combination with techniques from Artificial Intelligence,  Problem Structuring Methods, Geographic Information Systems, and Preference Learning as they pertain to MCDA decision processes. In this research program, we will design a spatial MCDA framework and develop, validate and evaluate tools to support the MCDA process in relation to the following  questions with applications related to smart sustainable cities: 1) What are the environmental characteristics, activities, factors and main difficulties that significantly influence the conduct of a MCDA process and how to deal with them? 2) How can the preferences of all stakeholders be captured and taken into account? 3) How can massive amount of quantitative and qualitative information, sometimes called big data, be integrated in the process? 4) How to evaluate the quality of a MCDA process? 5) How to explain and argue the decision process and the results to the stakeholders to ensure acceptability? Our research program will be conducted following a Design Science orientation. Our theoretical framework will be interdisciplinary and the underpinning philosophical paradigm is critical realism, a philosophy that is consistent with our multimethodological approach. We will apply and test our framework and tools in the following application domains: municipal asset management, drinking water source protection and social housing planning.

在当今的组织中，越来越多地需要透明度和问责制，尤其是对于涉及环境和公共资源的决策，这会影响具有潜水员脆弱性水平和利益冲突的群体。在城市规划和管理方面尤其如此，在饮用水源保护，废水管理，运输计划，社会住房计划或街道康复的问题上必须在越来越多的社会不平等和环境退化的背景下解决与人为活动有关的，以及在社交媒体，公民，公民参与和大数据的时代。在2010年代中期，这种情况导致了智能可持续城市的概念的出现，即“在信息和通信技术（ICT）支持的城市”以及对当地或环境限制的认识，满足其当前居民的需求，而无需损害其他世代或其他世代的能力或其他世代的需求，以满足他们的需求”（Höjer和Wangel，2015）。但是，一个城市如何发展朝着一个聪明的可持续城市发展呢？如何在利用ICT基础设施时确保可持续，健壮，严格，包容，透明，可接受和公正的决策如何进行公共决策过程？答案是跨学科的，部分在于分析领域，更准确地说，在参与多标准决策辅助（MCDA）（MCDA），这是一项运营研究的子学位，在过去的五个十年中，它在过去五个十年中的势头越来越不断提高，并且与人工智能，问题结构的方法相结合，与他们的技术相结合，与他们的技术相结合。在该研究计划中，我们将设计一个空间MCDA框架，并开发，验证和评估工具，以支持与以下问题有关的与智能可持续性城市相关的以下问题的关系：1）1）环境特征，活动，因素和主要难度有什么显着影响MCDA流程的行为以及如何处理它们？ 2）如何考虑所有利益相关者的偏好？ 3）如何将大量的定量和定性信息（有时称为大数据）集成到此过程中？ 4）如何评估MCDA过程的质量？ 5）如何解释和争论决策过程和结果，以确保可接受性？我们的研究计划将在设计科学取向后进行。我们的理论框架将是跨学科的，而基础的哲学范式是关键的现实主义，这种哲学与我们的多种方法论方法一致。我们将在以下应用领域中应用和测试我们的框架和工具：市政资产管理，饮用水源保护和社会住房计划。