Workshop: Predictive Modeling in Engineering; Texas A&M University; College Station, Texas; May 21-23, 2007

这笔资金用于于2007年5月21-23日在德克萨斯州A&A&M大学大学站举办一次研讨会，讨论与预测建模相关的问题。一个由大约40名参与者组成的小组，包括执业工程师、工程教育家、数学家和其他人，将讨论以下问题：对预测的基本理论(如概率论)是否存在共识？另类理论能否被排除在外？是否需要进行研究才能将适当的理论融入工程？这样的研究将解决哪些问题？是否需要工具(即软件)才能在工程中使用这一理论？这些工具可能是什么？如何将预测建模的原理引入工程实践和教育？工程教育学应该做出哪些改变？我们如何制定变革的激励措施？预测是所有决策的基础。理性预测是所有工程实践的基础，需要严格的建模方法。虽然一些专家认为只有概率论才能提供这种方法，但许多工程师教授和使用其他方法，包括确定性建模(完全忽略不确定性)、模糊逻辑、信念函数和确认论。而且，由于这些方法在其他相同的情况下产生高度矛盾的结果，它们不可能都是正确的。这次研讨会将为纠正目前的情况奠定基础。研讨会的结果将影响整个科学界和工程界，与采用预测性模型的所有学科都有关联。更重要的是，该研讨会有可能通过在存在不确定性的情况下建立根深蒂固的建模原则来深刻改变工程实践、研究和教育，这些原则将取代当今经常使用的特殊特征。

This grant provides funding to conduct a workshop May 21-23, 2007 at Texas A&M University, College Station, Texas, that will address issues related to predictive modeling. A group of about40 participants, including practicing engineers, engineering educators, mathematicians and others will address the following questions: Is there a consensus on a fundamental theory of prediction (such as probability theory)? Can alternative theories be excluded? Is research needed to incorporate the appropriate theory into engineering? What issues would such research address? Are tools needed (namely software) to enable the use of this theory in engineering? What might these tools be? How might the tenets of predictive modeling be introduced into engineering practice and education? What changes should be made to engineering pedagogy? How do we develop incentives for change? Prediction underlies all decision making. Rational prediction, which underlies all of engineering practice, demands a rigorous modeling approach. While some experts believe that only probability theory affords such an approach, many engineers teach and use alternative approaches, including deterministic modeling (the neglect of uncertainty altogether), fuzzy logic, belief functions and confirmation theory. And, since these methods yield highly contradictory results in otherwise identical situations, they all cannot possibly be correct. This workshop will set the stage for correcting the current situation. The findings of the workshop will impact the entire scientific and engineering communities, having relevance in all disciplines that employ predictive models. More importantly, this workshop has the potential to profoundly change engineering practice, research, and education by establishing well-grounded tenets of modeling in the presence of uncertainty that will displace the ad hoc characterizations often employed today.