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Optimal conditions were determined using an analytic method, stationary point of model was determined, and the determinant values of Hessian matrix showed that the response (yield of AMX elimination) agrees a maximum solution corresponding to optimal conditions, Tc = 488 °C, T = 33.6 °C, [AMX] = 58.5 mg·L-1 and [AC] 1.178 g·L-1, at which the predictive value of the response is ye = 100±3%3%.
The optimal conditions were determined using Taguchi method.
Optimal conditions were determined using experimental design techniques.
Optimal process conditions were determined using neural networks and genetic algorithm optimization.
Optimum conditions were determined using the response surface method (RS M and central composite face-centred design.
The temporal geometric shape, melting rates under various experimental conditions were determined using a photograph technique.
Similar(18)
Feasibility is assessed and operating conditions are determined using an extension of boundary-value methods.
Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach.
The governing equations and boundary conditions are determined using the energy method and Hamilton's principle.
The ice load in various conditions is determined using the ARCDEV data from the winter 1998 as the basic database.
Optimal cutting conditions was determined using the signal-to-noise (S/N) ratio which was calculated for Ra according to the "the-smaller-the-better" approach.
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