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

这项赠款提供资金进行研讨会2007年5月21日至23日在得克萨斯州A M大学，学院站，得克萨斯州，将解决有关预测建模的问题。 一组约40名参与者，包括执业工程师，工程教育工作者，数学家和其他人将解决以下问题：是否有一个基本的预测理论（如概率论）的共识？ 其他理论是否可以排除？ 研究是否需要将适当的理论纳入工程？ 这种研究将解决哪些问题？ 是否需要工具（即软件）来使这一理论在工程中得以应用？ 这些工具可能是什么？ 如何将预测建模的原则引入工程实践和教育？ 工程教育学应该做出哪些改变？ 我们如何激励变革？预测是所有决策的基础。 作为所有工程实践基础的合理预测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样的方法，但许多工程师教授和使用替代方法，包括确定性建模（完全忽略不确定性），模糊逻辑，置信函数和确认理论。 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状况奠定基础。 研讨会的结果将影响整个科学和工程界，与采用预测模型的所有学科都有关联。 更重要的是，这个研讨会有可能深刻地改变工程实践，研究和教育，通过建立良好的建模原则，在不确定性的存在，将取代今天经常采用的特设表征。

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.