Quadratic Optimization under Uncertainty with applications

机译：不确定性下的二次优化及其应用

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Over the years, a great deal of attention has been focussed on studying constrained quadratic optimization problems due to its importance in applications. However, these studies have so far been limited mainly to problems under no data uncertainty, despite the reality of data uncertainty in many real-world problems due to modeling or prediction errors.

机译：多年以来，由于其在应用中的重要性，因此已将大量注意力集中在研究约束二次优化问题上。但是，尽管在许多现实世界中由于建模或预测错误导致的数据不确定性的现实，但迄今为止，这些研究主要限于没有数据不确定性的问题。

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来源
《The 8th international conference on optimization: Techniques and Applications》|2010年|105|共1页
会议地点 Shanghai(CN)
作者
V.Jeyakumar;
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作者单位

Department of Applied Mathematics,University of New South Wales, Sydney 2052, Australia;

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原文格式 PDF
正文语种 eng
中图分类系统优化;
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Quadratic Optimization under Uncertainty with applications

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