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可再生能源发电技术的发展以及在电网中日益普及的分布式电源（DG）给电力系统带来了更多不确定性，使电力系统状态估计量测数据不足的问题更加突出。当前多采用对DG进行伪量测建模的方法来提高系统量测冗余度，针对同时考虑DG之间的不确定性和相关性的伪量测建模研究相对薄弱的现状，提出了一种基于Pair-Copula风电功率相关性模型和高斯混合模型（Gaussian mixture model,GMM）等效不确定性模型的DG伪量测建模方法，该方法可以考虑复杂的DG出力相关性和不确定性，提高伪量测的准确性从而提高配电网状态估计的精确度。通过对经修改的IEEE-14节点算例系统进行仿真计算，说明所提方法能够合理刻画状态估计问题中分布式电源的出力不确定性与相关性，计算结果验证了所提方法的有效性。

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An embedded face recognition system is designed to solve the problems of attendance by IC card or fingerprint in management system.The system adopts S3C2440 as the ARM9 development board of microprocessor chip. Through cross-compilation and transplantation of Linux operating system, the improved Adaboost face detection algorithm and the convolutional neural network VIPLFaceNet face recognition algorithm are selected for detection and recognition.Experiments on FDDB face database show that the accuracy of Adaboost face detection algorithm is 80.5%, and that of the improved one is 87.1%. The system can effectively verify the identity of the vehicle soldier and meet the requirements of the driver training management system. [ABSTRACT FROM AUTHOR]

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