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首页> 外文期刊>The Journal of Organic Chemistry >GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward
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GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward

机译:GIAO C-H COZY模拟与人工神经网络模式识别分析合并。推动结构验证向前迈进

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摘要

The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN) mediated multidimensional pattern recognition from experimental and calculated 2D C-H COSY. In order to identify subtle errors (such as regio- or stereochemical), more than 400 ANNs have been built and trained, and the most efficient in terms of classification ability were successfully validated in challenging real examples of natural product misassignments.
机译:使用量子化学方法(确认或拒绝候选结构)的结构验证问题已通过人工神经网络(ANN)介导的多维二维模式识别从实验和计算的2D C-H COSY中解决。为了识别细微的错误(例如区域或立体化学),已经构建并训练了400多个人工神经网络,并且在具有挑战性的天然产物错配的真实示例中,成功验证了最有效的分类能力。

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