4. Intensity Measure Selection
The imselection class evaluates and ranks intensity measures (IMs) using the
information-theoretic framework of Ebrahimian & Jalayer (2021). The central metric
is the Relative Sufficiency Measure (RSM), expressed in bits: a positive
RSM(IM₂ vs IM₁) means IM₂ is the more sufficient IM. Two complementary metrics
are also provided — efficiency (βD|IM) and proficiency (βIM|DCR=1). Both Modified
Cloud Analysis (MCA) and Incremental Dynamic Analysis (IDA) workflows are supported.
- 4.1. Initialisation
- 4.2. Efficiency — Modified Cloud Analysis
- 4.3. Efficiency — Incremental Dynamic Analysis
- 4.4. Proficiency — Modified Cloud Analysis
- 4.5. Proficiency — Incremental Dynamic Analysis
- 4.6. Relative Score Method — Modified Cloud Analysis
- 4.7. Relative Score Method — Incremental Dynamic Analysis
- 4.8. Relative Score Method — General
- 4.9. IM Comparison
4.10. References
Ebrahimian, H. and Jalayer, F. (2021). “Selection of seismic intensity measures for prescribed limit states using alternative nonlinear dynamic analysis methods”, Earthquake Engineering and Structural Dynamics, 50(5), 1235-1250. https://doi.org/10.1002/eqe.3393
Luco, N. and Cornell, C.A. (2007). “Structure-specific scalar intensity measures for near-source and ordinary earthquake ground motions.” Earthquake Spectra, 23(2), 357–392.
Shome, N. and Cornell, C.A. (1999). “Probabilistic seismic demand analysis of nonlinear structures.” Report No. RMS-35, Stanford University, Stanford, CA.
Padgett, J.E., Nielson, B.G., and DesRoches, R. (2008). “Selection of optimal intensity measures in probabilistic seismic demand models of highway bridge portfolios.” Earthquake Engineering & Structural Dynamics, 37(5), 711–725.