Fundamental studies and their applications for ontological engineering and decision support systems for energy production and pollution processing systems

国家媒体广泛报道了对加拿大落后生产力的担忧。 鉴于石油和天然气行业在加拿大的重要性，该行业生产力下降的重大社会经济影响和成本需要经济研发部门的紧急关注。 有人认为，加拿大工业生产率下降的原因是，与美国相比，我们对信息和通信技术的投资相对较低（地球仪& Mail，2005年9月9日）。 拟议的研究计划将解决这一问题，通过加强对有关的问题和先进的信息技术的发展和应用，以提高工业生产过程的生产力的理解。 该计划旨在建立基础设施，以支持基于知识的决策支持系统的建设，帮助操作人员和管理人员在工业过程中执行复杂的任务。 研究目标包括：（a）开发本体工程的方法和工具，支持建立智能决策支持系统的知识基础，（B）开发人工智能和基于知识的系统技术，用于能源生产和污染处理系统的建模和分析。开发的先进计算解决方案将有助于提高加拿大工业中一些与石油和二氧化碳有关的流程的生产力和效率，这些行业迫切需要提高生产力的成本效益手段。

Concerns about Canada's laggard productivity have been widely reported in the national media.  Given the importance of the oil and gas industry in Canada, the significant socio-economic impacts and costs of declining productivity in the industry requires urgent attention from the R&D sector of the economy.  It has been suggested that the reduced productivity in Canadian industries is due to our relatively low investments in information and communications technologies compared to the United States (Globe & Mail, Sept 9, 2005).  The proposed research program will address this concern by enhancing understanding of issues and problems related to development and application of advanced information technologies for improving productivity of industrial processes.  This program aims to build infrastructure for supporting construction of knowledge-based decision support systems, which assist operators and managers in performing complex tasks in industrial processes.  The research objectives include: (a) developing methods and tools for ontological engineering, which support building the knowledge foundations for intelligent decision support systems, and (b) developing artificial intelligence and knowledge-based system technologies for modeling and analysis of energy production and pollution processing systems. The advanced computing solutions developed will help enhance productivity and efficiency of some petroleum- and carbon dioxide-related processes in Canadian industries, which are in urgent need of cost-effective means of improving productivity.