Knowledge engineering principles for the effective management of complex systems

有效管理复杂系统的知识工程原理

• 批准号: 250239-2008
• 负责人: Guergachi, Aziz
• 金额: $ 1.56万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=503496
• 关键词: Knowledge; engineering; principles; effective; management

This research focuses on investigating advanced machine learning techniques with applications to engineering and business management. In the engineering area, we look at the analysis of the risk of failure of drinking water facilities. Contrary to what one may think, waterborne disease outbreaks in developed countries seem to continue to occur on a relatively regular basis. The reason for this phenomenon is not the lack of adequate treatment technologies. Rather it is the cumulative impact of a sequence of small individual events, each of which is relatively harmless on its own, that leads to the outbreak - hence the systemic nature of the causes of the failures, and the relevance of machine learning techniques such as kernels and pattern recognition algorithms (for the classification of a sequence of events as 'collapse-oriented' or 'survival-oriented'). In the business management area, the focus is on the topic of sales forecasting and management, which has a direct connection with the issue of job losses in the manufacturing sector in Ontario. This type of job losses is a direct consequence of the drop in manufacturing sales, which is itself due to the appreciation of the Canadian dollar against the United States dollar. Such an appreciation leads indeed to the odd situation where Canadian products suddenly become more expensive for American customers, while the value-adding features of these very same products have not changed at all - hence the drop in sales. Laying-off workers has so far been the quickest way, for manufacturers, to react to this drop in sales. There is, however, no evidence that the laying-off of workers is the optimal control action (in the control-theoretic sense of the term) to react to currency appreciation. The applicant and his co-workers developed a quantified system to help salespeople and managers analyze their interactions with customers, develop sales forecasts and design adequate action plans for the future. In this project, we intend to investigate both of these applications using the state-of-the-art techniques for machine learning, knowledge representation and pattern analysis.

这项研究的重点是研究先进的机器学习技术，并将其应用于工程和商业管理。在工程领域，我们着眼于分析饮用水设施故障的风险。与人们可能认为的相反，发达国家的水传播疾病爆发似乎继续相对定期地发生。造成这一现象的原因并不是缺乏适当的处理技术。相反，它是一系列小的个体事件的累积影响，其中每个事件本身相对无害，导致爆发-因此故障原因的系统性，以及机器学习技术的相关性，如内核和模式识别算法（用于将事件序列分类为“面向灾难”或“面向生存”）。在商业管理领域，重点是销售预测和管理，这与安大略制造业的失业问题有直接联系。这类失业是制造业销售下降的直接后果，而制造业销售下降的原因是加元对美元升值。这种升值确实导致了一种奇怪的情况，即加拿大产品对美国消费者来说突然变得更贵，而这些产品的增值特征根本没有改变，因此销售额下降。到目前为止，裁员是制造商应对销售下滑的最快方式。然而，没有证据表明解雇工人是应对货币升值的最佳控制行动（在控制理论意义上）。申请人和他的同事开发了一个量化系统，帮助销售人员和经理分析他们与客户的互动，制定销售预测，并为未来设计适当的行动计划。在这个项目中，我们打算使用最先进的机器学习，知识表示和模式分析技术来研究这两种应用。