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• W2032220389 abstract "We present in this study a new and robust algorithm for feed-forward neural network (NN) fitting. This method is developed for the application in potential energy surface (PES) construction, in which simultaneous energy-gradient fitting is implemented using the well-established Levenberg–Marquardt (LM) algorithm. Three fitting examples are demonstrated, which include the vibrational PES of H2O, reactive PESs of O3 and ClOOCl. In the three testing cases, our new LM implementation has been shown to work very efficiently. Not only increasing fitting accuracy, it also offers two other advantages: less training iterations are utilized and less data points are required for fitting." @default.
• W2032220389 created "2016-06-24" @default.
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• W2032220389 date "2015-06-01" @default.
• W2032220389 modified "2023-09-24" @default.
• W2032220389 title "An implementation of the Levenberg–Marquardt algorithm for simultaneous-energy-gradient fitting using two-layer feed-forward neural networks" @default.
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• W2032220389 doi "https://doi.org/10.1016/j.cplett.2015.04.019" @default.
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