A pressured microwave-assisted hydrolysis （PMAH） technique has been developed for hydrolyzing the crude glycyrrhizic acid （GA） extracted from licorice root to prepare glycyrrhetinic acid （GRA）. In order to optim...A pressured microwave-assisted hydrolysis （PMAH） technique has been developed for hydrolyzing the crude glycyrrhizic acid （GA） extracted from licorice root to prepare glycyrrhetinic acid （GRA）. In order to optimize the efficiency of PMAH, several experimental parameters were investigated, including liquid-solid ratio, hydrolysis time, sulfuric acid concentration and hydrolysis temperature. The optimized hydrolysis conditions were as follows：pressured microwave-assisted hydrolysis of crude GA for 21 min （taking 15 min to reach 150 ℃, and holding it for 6 rain） at 150 ℃ （at a radiation power of 450 W） in 3%-5% sulfuric acid solution with the liquid-solid （ml.g-1 crude GA） ratio of 25 ： 1. As a result of the considerable saving in time and higher product yields （up to 90%）, PMAH was proved more effective than conventional methods.展开更多
In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-...In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.展开更多
基金Supported by the Yunnan Provincial Department of Education Key Foundation (07Z10311)
文摘A pressured microwave-assisted hydrolysis （PMAH） technique has been developed for hydrolyzing the crude glycyrrhizic acid （GA） extracted from licorice root to prepare glycyrrhetinic acid （GRA）. In order to optimize the efficiency of PMAH, several experimental parameters were investigated, including liquid-solid ratio, hydrolysis time, sulfuric acid concentration and hydrolysis temperature. The optimized hydrolysis conditions were as follows：pressured microwave-assisted hydrolysis of crude GA for 21 min （taking 15 min to reach 150 ℃, and holding it for 6 rain） at 150 ℃ （at a radiation power of 450 W） in 3%-5% sulfuric acid solution with the liquid-solid （ml.g-1 crude GA） ratio of 25 ： 1. As a result of the considerable saving in time and higher product yields （up to 90%）, PMAH was proved more effective than conventional methods.
文摘In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.
