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• W2037158581 startingPage "52" @default.
• W2037158581 abstract "Traditional error back propagation is a widely used training algorithm for feed forward neural networks (FFNNs). However, it generally encounters two problems of slow learning rate and relative low accuracy. In this work, a hybrid genetic algorithm combined with modified Levenberg–Marquardt algorithm (HGALM) was proposed for training FFNNs to improve the accuracy and decrease the time depletion comparing to the traditional EBP algorithm. The FFNNs based on HGALM were used to predict the binodal curve of water–DMAc–PSf system and protein solubility in lysozyme–NaCl–H2O system. The results would be used for guiding experimental researches in preparation of asymmetry polymer membrane and optimization of protein crystal process." @default.
• W2037158581 created "2016-06-24" @default.
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• W2037158581 date "2005-11-01" @default.
• W2037158581 modified "2023-10-16" @default.
• W2037158581 title "Prediction of phase equilibrium properties for complicated macromolecular systems by HGALM neural networks" @default.
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• W2037158581 doi "https://doi.org/10.1016/j.fluid.2005.09.017" @default.
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