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, a linear or a quadratic polynomial is determined. The obtained response surface model serves then to determine the optimal combination of design variables by solution of a constrained mathematical program where use is made of the command fmincon
-COSANO , G. , G ARCIÁ-GIMENO , R.M. , R ODRÍGUEZ-PÉREZ , R. & H ERVÁS-MARTÍNEZ , C. ( 2006 ): Performance of response surface model for prediction of Leuconostoc mesenteroides growth parameters under different experimental conditions . Food Control
.52 28. 7 2 2 9 5 5 20 0.48 29. 7 2 2 10 5 5 5 0.43 30. 6 1 1 10 5 20 20 0.5 31. 6 1 2 9 5 5 20 0.51 32. 7 2 2 9 5 20 5 0.46 33. 7 2 2 10 15 20 5 0.5 34. 7 1 2 9 5 20 20 0.47 Response surface modeling by Box-Behnken Design (BBD) The effect of toluene
Determination of the individual specific heat capacities of solids from multi-component powder mixtures and polymorphic mixtures
A combined analysis of quantitative PXRD and calorimetry measurements
.1021/ac0263622 . 5. Tjahjono , M , Guo , L , Garland , M . The development of a response surface model for the determination of infinite dilution partial molar volumes and excess
.00 85.3 200 20 4.00 87.5 Table 3. Main effects and interactions of the response surface models Regression coefficient Moisture Volatiles retention Intercept 5.92 77.67 XT -0.64** 5.47** XC -0.31* 4.35** XT2 -0.43* 1.74 XC2 -0.33 0.69 X T X C -0.24 -1
-60.6.610 Zurera-Cosano , G. , Garciá-Gimeno , R.M. , Rodríguez-Pérez , R. , and Hervás-Martínez , C. ( 2006 ). Performance of response surface model for prediction of L. mesenteroides growth parameters under different experimental
increases with temperature dissimilar to other metallic materials. To be able to quantify the influence of temperature on helical spring response, explicit response surface models based on nonlinear regression of the results given in Table
