The phrase "adaptability of the model" is correct and usable in written English.
It can be used when discussing the flexibility or ability of a model to adjust to different conditions or inputs.
Example: "The adaptability of the model allows it to perform well in various scenarios, making it a valuable tool for researchers."
Alternatives: "flexibility of the model" or "versatility of the model".
The model is shown to be compatible with all three release devices, highlighting easy adaptability of the model to virtually any release system and geometry.
For improving the adaptability of the model, the weighted parameter between them is then designed according to the gradient information of image.
Based on obtained results, designed ANFIS model has good accurate and able to predict wax deposition thickness in single-phase turbulent flow rate, because of the integration of fuzzy logic systems with the capability of learning in artificial neural networks which leads to the adaptability of the model with this issue.
Increasing complexity may improve the adaptability of the model to fit more of the existing data [30], but simultaneously boost the sensitivity of the model [32].
The adaptability of the compartmental model allows the simulation of human or animal subjects and VEGF-dependent diseases as long as the biological properties of the studied tissue are available.
The main advantages of the control volume approach are the adaptability of the entire model and the fast computational speed in comparison to elaborate fluid dynamics models.
The effectiveness and good adaptability of the proposed model are verified based on the agreement between the numerical simulation and shaking table test results.
In this section, we discuss the adaptability of the proposed model.
The interpretation of the results shows the adaptability of the dicenter model for these extreme conditions.
Finally, to further show the effectiveness and adaptability of the proposed model, we apply it to denoise four images of size 128 × 128 contaminated by Gaussian noise with different standard deviations (σ = 5,10,15, and 20).
In order to enhance the flexibility and adaptability of the DTMS model, a comprehensive parameter optimization method is proposed, which incorporates particle swarm optimization (PSO) with Kalman filter and maximum likelihood method for estimating the states and parameters of DTMS model.
