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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.

The Xixiayuan project is a regulating reservoir in china. The concrete dam section is constructed on soft rock foundation. In this paper, we present the case study on the treatment for the soft rock foundation. The treatment includes the construction of concrete cut-off wall, reinforcement by dynamic compaction method, and installation of the stone columns. The treatment was justified by the field instruments installed in the foundation. The measured data show that the treatment can reduce significantly the settlement at the foundation. Moreover, layered settlement was employed in the analysis. The results demonstrate that very small total and differential settlement occurred in the foundation. The analysis illustrate the success of the treatment for the soft rock dam foundation, and useful for gaining experience for future designs and analysis.