Improved L-M algorithm for ANNs prediction of phase equilibrium in macromolecule system

Xuezhong He, Xiangping Zhang, Suojiang Zhang*, Chunshan Li, Jindun Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Error back propagation (EBP) is a widely used training algorithm for feedforward neural networks (FFNNs), but low learning rate limits its applications in the networks with complex topology architecture and large patterns. In this work, two modifications on Levenberg-Marquardt algorithm for FFNNs were made. One modification was made on the objective function, while the other was the evaluation of the initial weights and biases. The modified algorithm gave a better convergence rate compared to the traditional EBP algorithm and it was less computationally intensive and required less memory. The performance of the algorithm was verified separately with polymer and protein systems. The results showed that the BP network based on modified Levenberg-Marquardt algorithm could be used to predict the binodal curve of H2O/DMAc (N,N-dimethylacetamide) /PSf (polysulfone) system and lysozyme solubility in aqueous salt solution.

Original languageEnglish
Pages (from-to)393-399
Number of pages7
JournalHuagong Xuebao/CIESC Journal
Volume56
Issue number3
StatePublished - Mar 2005
Externally publishedYes

Keywords

  • BP network
  • EBP algorithm
  • Levenberg-Marquardt algorithm
  • Macromolecule system

Fingerprint Dive into the research topics of 'Improved L-M algorithm for ANNs prediction of phase equilibrium in macromolecule system'. Together they form a unique fingerprint.

Cite this