The phrase "adaptive formulations" is correct and usable in written English.
It can be used in contexts where you are discussing methods, strategies, or approaches that adjust or change based on specific conditions or requirements.
Example: "The research team developed adaptive formulations to address the varying needs of patients in different demographics."
Alternatives: "flexible formulations" or "dynamic formulations".
A solution is to leverage data driven control algorithms, which, in their adaptive formulation, can self-tune to uncertain environments.
This uncoupling of the geometry mapping from the finite element approximation leads to a naturally p-adaptive formulation, well suited to parallelization, which can be implemented on unstructured, coarse meshes of high-degree elements to obtain accurate and numerically stable solutions.
TESSEMA and YEN [11] designed an adaptive penalty formulation where the feasible proportion of the current population was utilized to tune the penalty factor.
Three-dimensional finite element models are developed to predict stress singularity at the crack tip, including an adaptive mesh formulation along with isoperimetric quadratic elements.
More research is needed to better understand the relationship between climate change and transmission of mosquito-borne diseases, and to further promote adaptive policies formulation to reduce unexpected climate-related risk at a global, regional or local level.
A two-dimensional single-phase cathode electrode model that accounts for voltage losses across the electrolyte and solid phases and water and oxygen concentrations is implemented using an adaptive finite element formulation.
In all previous composite adaptive controllers, the formulation of the prediction error is predicated on the critical assumption that the system uncertainty is linear in the uncertain parameters (LP uncertainty).
The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed.
The reinforcement learning (RL) paradigm is a powerful framework which has been applied in different formulations of adaptive control strategies for AUVs.
It basically connects homeostatic imperatives with classical (utilitarian and control theoretic) formulations of adaptive behaviour.
