CAREER: Adaptive Higher-Order Error Correction of NonlinearDiffusion Generalized Perturbation Theory Via a Neural Network

职业：通过神经网络对非线性扩散广义扰动理论进行自适应高阶误差校正

• 批准号: 9624687
• 负责人: Guillermo Maldonado
• 金额: $ 31万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-08-01 至 2001-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9624687&HistoricalAwards=false
• 关键词: CAREER; Adaptive; Higher; Order; Error

9624687 Maldonado The general objective of the proposed research is to initiate a research program that would promote, extend, and improve recent advances in Generalized Pertarbatium Theory Techniques. The long-term goal of this project targets to exploit more general and multidisciplinary applications, while the near-term goal will target the development of an adaptive -and computationally economic- error reduction technique applicable to an nth order perturbation theory methodology. The preliminary results herein presented strongly suggest that a relatively rudimentary two-hidden-layer artificial neural network (ANN) can be suitably trained for this type of application. In fact, the GPT methodology previously developed by the PI provides a unique framework for the systematic training and adaptive implementation of an ANN designed to predict, and thus correct, the error associated with an nth order GPT solution. Moreover, identifying all portions of these calculations which can take advantage of massively parallel or scalable computers will also be addressed. The main objective of the PI's education plan revolves around nurturing four major ongoing career activities which he has identified as key contributing factors to the future success of his education plan. Furthermore, these activities have been selected exclusively by the PI based upon several moths of hands-on assessments and observations, and re in full agreement with his personality, background, and known talents. The PI enjoys these activities and seeks no personal gain from them other than selfulfillment as a person and as an educator. These activities, listed in no particular order of preference or implied importance, are: Active Learning Techniques. Encouraging Underrepresented Groups into Science and Engineering. Involving Undergraduate Students in Research. International Extensions of Research Efforts. The education plan of this proposal elaborates further on each of the above topics.

9624687马尔多纳多（Maldonado）拟议的研究的一般目标是启动一项研究计划，该计划将促进，扩展和改善广义pertarbatium理论技术的最新进展。 该项目的长期目标是利用更一般和多学科的应用程序，而近期目标将针对适用于适用于第n阶扰动理论方法的自适应和计算经济误差技术的发展。 本文提出的初步结果强烈表明，可以适当地训练相对基本的两层人工神经网络（ANN）。 实际上，以前由PI开发的GPT方法论为系统训练和自适应实现ANN提供了一个独特的框架，旨在预测与Nth阶GPT解决方案相关的错误。 此外，还将解决这些计算的所有部分，这些计算可以利用大量并行或可扩展的计算机。 PI教育计划的主要目标围绕着培育四项主要正在进行的职业活动，他认为这是他教育计划未来成功的关键因素。 此外，这些活动是根据几个动手评估和观察的飞蛾完全由PI选择的，并与他的个性，背景和已知才能完全同意。 PI喜欢这些活动，除了作为一个人和教育工作者的Selfulflyment以外，他们没有寻求个人收益。 这些活动（没有特殊的偏好或暗示重要性顺序列出）是：主动学习技巧。鼓励代表性不足的群体进入科学和工程。让本科生参与研究。国际研究工作的扩展。 该提案的教育计划进一步阐述了上述每个主题。