Application of an artificial immune algorithm on a statistical model of dam displacement

作者：Xi Guang yong^*; Yue Jian ping; Zhou Bao xing; Tang Pu

来源：Computers & Mathematics with Applications, 2011, 62(10): 3980-3986.

DOI：10.1016/j.camwa.2011.09.057

• Deformation monitoring
• Statistical model
• Artificial immune algorithm
• Immune statistical model

Statistical analysis is a useful method for setting the whole string of dam displacement measures in mathematical expressions. A statistical model is usually obtained by the method of stepwise regression. The stepwise regressions based on the least square method have limitations such as the lack of stability of the set of selected variables and bias in the parameter estimates. However, the Artificial Immune Algorithm (AIA) provides good performance as an optimization algorithm. This paper proposes an immune statistical model, which merges the statistical model and the immune algorithm together, to resolve the data analysis problems of dam horizontal crest upstream-downstream displacement. The stepwise regression model and immune statistical model have been compared, showing that the immune statistical model provide a higher degree of accuracy in predicting the future behavior of the dam.

• 出版日期2011-11
• 单位河海大学