Development and application of robust estimation and artificial intelligence strategies on noisy and unreliable data

拟议的研究涉及圭尔夫大学（UofG；圭尔夫，安大略省）的智能控制和估计（ICE）实验室（Gadsden博士），Adastra公司（安大略省多伦多）和Minetell（安大略省多伦多）之间的合作关系。合作研究伙伴关系的主要目标是开发和应用鲁棒估计和人工智能（AI）策略，以处理工业中发现的嘈杂和不可靠的数据。潜在的结果和影响包括：1)基于人工智能策略和新的估计方法的新算法和技术的发展；2)改进人工智能算法对虚假或异常数据的检测；3)开发可用于多种行业的状态监测策略，包括但不限于航空航天、信息管理、制造业和采矿业；4)将人工智能研究发现转化为公共和私营部门的可能性，这将为加拿大带来社会经济效益；5)培养高素质人才（High Quality Personnel， HQP），使其成为未来人工智能领域的领导者和员工。

The proposed research involves a partnership between the Intelligent Control and Estimation (ICE) Laboratory (Dr. Gadsden) at the University of Guelph (UofG; Guelph, Ontario), Adastra Corporation (Toronto, Ontario), and Minetell (Toronto, Ontario). The primary goal of the collaborative research partnership is to develop and apply robust estimation and artificial intelligence (AI) strategies on noisy and unreliable data found in industry. The potential outcomes and impacts include: 1) development of new algorithms and techniques based on AI strategies and a novel estimation method; 2) improved detection of false or anomalous data used by AI algorithms; 3) development of condition monitoring strategies that can be used in a variety of industries, including but not limited to aerospace, information management, manufacturing, and mining; 4) possibility to translate AI research discoveries in the public and private sectors, which will lead to socio-economic benefits for Canada; and, 5) training of High Quality Personnel (HQP) as future leaders and employees in the AI field.