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This study has utilized the response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) approaches for the modeling of polymer solution viscosity.
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In this paper, topology optimization and parameter optimization utilizing the response surface method (RS M are applied for the optimum design of the jig reinforcement structure, in order to minimize the total jig weight while securing the dimension precision of the foamed urethane case.
Utilizing the Response Surface Methodology (RS M with three factors Central Composite Design (CCD), this paper demonstrates the sustainable model of characterizing the Signal to Noise Ratio (SNR) through second order quadratic model in measuring the acoustic signal through Acoustic Doppler Velocimeter (ADV).
The sensitivity analysis invoking the CPU time-consuming finite element analyses is replaced with the genetic evolution and the fitness of each genome in the population is evaluated by utilizing the response surfaces of objective functions approximated by ANN.
This study utilizes the dual response surface approach to quantify variability in critical performance characteristics during conceptual design phase of a launch vehicle.
Furthermore, to achieve the predicted model and prepare the optimum condition of the process, the central composite design of the response surface methodology was utilized.
A validated numerical model is applied to calculate the tension force of mooring system for both the single-cage system and the multi-cage system at several sea states, and the response surface method is utilized to display the limit state function to calculate the reliability level in terms of the uncertain metocean variables.
Design-expert software was utilized to set up the groundwork for the response surface methodology (RS M.
The regression model, the response surface model, is utilized to create more data.
In this paper, the response surface method (RS M is utilized to formulate the complex design problem.
Full factorial design and central composite design (CCD) from the response surface methodology (RS M were utilized in the screening and optimization of the system.
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