The phrase "adopted to optimize" is correct and usable in written English.
It can be used when discussing methods, strategies, or practices that have been implemented to improve efficiency or effectiveness.
Example: "The new software was adopted to optimize our workflow and reduce processing time."
Alternatives: "implemented to enhance" or "adopted for improvement".
Particle swarm optimization is adopted to optimize the parameter settings through the well-trained BP model, where each particle is assessed using fitness function.
Both dual- and triple-objective optimizations were adopted to optimize the shape of the inlet/outlet diffusion segment, the response surface methodology (RSM) was used to generate approximate functions relating to the objectives and design parameters, and the non-dominated sorting genetic algorithm (NSGA-II) was selected to conduct the optimizations.
Bothe single objective and multi-objective optimization are adopted to optimize the configurations of multi rows film cooling holes, and the Multi-Island Genetic Algorithm and The response surface approximation with the Non-dominated Sorting Genetic Algorithm (NSGA-II) are selected to conduct the optimizations.
An optimization study adopted to optimize the operating parameters, such as temperature and fuel composition using a differential evolution algorithm.
In order to prevent the interaction between two types of variables and enhance global search ability of traditional particle swarm optimization (PSO), intelligent single particle optimizer (ISPO) is adopted to optimize this model.
Further, different optimization methods are adopted to optimize TMD parameters when considering different performance indices.
The rated power, capacity, location of BESS, and three operation strategy control variables are decision variables, and intelligent single particle optimizer (ISPO) is adopted to optimize this model.
In order to prevent the interaction between two types of variables and enhance global search ability, intelligent single particle optimizer (ISPO) is adopted to optimize this model.
The model of DFIG for small signal stability analysis was presented in [3] and the particle swarm optimization (PSO) method was adopted to optimize the controller parameters.
The particle swarm optimization (PSO) [11, 12] and mixed integer PSO [13] techniques are adopted to optimize the wind farm layout in terms of optimal placement allocation of WTs.
Meanwhile, the optimization algorithms inclusive of genetic, grid and quadratic are adopted to optimize the important parameters of C-SVC and υ-SVC, such as C, υ and γ, so as to improve the classification performance and generalization ability of the predictive model of support vector machine.
