Genetic Programming Based on an Adaptive Regularization Method

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Wu:2006:iccis,

• author = "Yanling Wu and Jiangang Lu and Youxian Sun",
• title = "Genetic Programming Based on an Adaptive Regularization Method",
• booktitle = "International Conference on Computational Intelligence and Security, 2006",
• year = "2006",
• volume = "1",
• pages = "324--327",
• address = "Guangzhou",
• month = nov,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-4244-0605-6",
• DOI = "doi:10.1109/ICCIAS.2006.294148",
• abstract = "A proper model of a bioprocess is very important for the development of industrial bioprocesses. Here, genetic programming (GP) and genetic algorithm (GA) are used to model the Avermectin fermentation process. To get more accuracy model without losing generalisation, a regularisation term is integrated into the fitness function and an adaptive method to optimise regularisation parameter is proposed to balance training accuracy and the curvature of a nonlinear model. Furthermore, a new protected approach is proposed and experiments show that with the method, the amount the undesired sharp changes in the predicting value decreases largely",
• notes = "National Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou",

}

Genetic Programming entries for Yanling Wu Jiangang Lu Youxian Sun

Citations