A Self-adapting Algorithm for Identifying Rheology Model and Its Parameters of Rock Mass
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @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