A Self-adapting Algorithm for Identifying Rheology Model and Its Parameters of Rock Mass

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Chen:2009:CINC,

• author = "Bing-Rui Chen and Xia-Ting Feng and Cheng-Xiang Yang",
• title = "A Self-adapting Algorithm for Identifying Rheology Model and Its Parameters of Rock Mass",
• booktitle = "International Conference on Computational Intelligence and Natural Computing, CINC '09",
• year = "2009",
• month = jun,
• volume = "2",
• pages = "478--481",
• keywords = "genetic algorithms, genetic programming, Jinping-2 hydropower station, chaos-genetic algorithm, hybrid genetic programming, optimal rheological model, rheology model identification, rock mass parameters, self-adapting system identification method, tentative model, identification, natural resources, rheology",
• DOI = "doi:10.1109/CINC.2009.39",
• abstract = "As it is difficult to previously determine rockmass rheology constitutive model using phenomena methods of mechanics, so a new self-adapting system identification method, a hybrid genetic programming (GP) with the chaos-genetic algorithm (CGA) based on self-rheological characteristic of rock mass, is proposed. Genetic programming is used for exploring the model's structure and the chaos-genetic algorithm is produced to identify parameters (coefficients) in the tentative model. The optimal rheological model is determined by mechanical and rheological characteristic, important expertise etc and can describe rheological behavior of identified rock mass perfectly. The assistant tunnel B of Jinping-2 hydropower station is used as an example for verifying the proposed method. The results show that the algorithm is feasible and has great potential in finding new rheological models.",
• notes = "Also known as \cite{5230917}",

}

Genetic Programming entries for Bing-Rui Chen Xia-Ting Feng Chengxiang Yang

Citations