The phrase "adaptive importance" is correct and usable in written English.
It can be used in contexts discussing the significance or relevance of adaptability in various fields, such as biology, psychology, or organizational behavior.
Example: "In evolutionary biology, the adaptive importance of certain traits can determine an organism's survival and reproductive success."
Alternatives: "significance of adaptability" or "relevance of adaptability".
Recently, Andersen et al. [ 20] identified the molecular basis as well as the different oxygen binding properties of the haemoglobin alleles, thereby providing the important link between genotypes and phenotypes of adaptive importance.
Recent work in adaptive importance sampling is applied to Markov chain models for Monte Carlo simulations.
Adaptive importance sampling is used to determine the cumulative-time system failure probability.
We present in this paper an adaptive importance sampling algorithm to tackle these challenges.
An adaptive importance sampling methodology is proposed to compute the multidimensional integrals encountered in reliability analysis.
In this article, we develop a Kriging-based adaptive Importance Sampling approach for rare event probability estimation.
In their recent work, Martino, Elvira et al. proposed adaptive population importance sampling [22] and gradient adaptive population importance sampling [23] that adapt the mean and the covariance of proposal Gaussian pdfs, and reported significant improvements with respect to MIS that keeps the individual proposal pdfs fixed.
Further, region-wise assessment may also be useful in adaptive feature importance weighting schemes.
Cornuet et al. [20] improve this in their adaptive multiple importance sampling algorithm and present optimal exploitation of previous samples, which automatically stabilizes the process.
In this paper an adaptive radial-based importance sampling (ARBIS) method is presented.
An adaptive multi-modal importance sampling technique is developed for efficiency and accuracy in probabilistic life estimation under MSD due to corrosion fatigue.
