| 引用本文: | 李春雨,刘伟朋,郑爱竹,邱智东,石羽文,姜孟成,李钠,贾艾玲.基于AHP-CRITIC法结合BP神经网络-遗传算法优化参莲草方提取工艺[J].中国现代应用药学,2025,42(7):58-66. |
| lichunyu,Liuweipeng,zhengaizhu,Qiuzhidong,shiyuwen,jiangmengcheng,lina,Jia Ailing.Optimization of ShengLian Cao extraction process based on AHP-CRITIC method combined with BP neural network-genetic algorithm[J].Chin J Mod Appl Pharm(中国现代应用药学),2025,42(7):58-66. |
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| 基于AHP-CRITIC法结合BP神经网络-遗传算法优化参莲草方提取工艺 |
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李春雨1, 刘伟朋1, 郑爱竹2, 邱智东1, 石羽文1, 姜孟成1, 李钠1, 贾艾玲1
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1.长春中医药大学药学院;2.长春中医药大学第三附属医院
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| 摘要: |
| 目的 利用 BP神经网络-遗传算法结合AHP-CRTIC法优选参莲草颗粒提取工艺。方法 以去乙酰车叶草苷酸甲酯、野黄芩苷、出膏率为指标,以AHP-CRITIC法确定各指标混合权重系数,基于Box-Behnken 响应面试验设计,以BP神经网络-遗传算法对参莲草方提取过程中加水倍数、提取时间、提取次数的非线性影响进行反映,确定最佳提取工艺,并对优化结果进行工艺验证。结果 BP神经网络-遗传算法优选结果为加水倍数8倍、煎煮时间1.5h、煎煮次数2次,验证试验显示其综合评分为93.24。结论 基于BP神经网络-遗传算法优选的参莲草方提取工艺稳定可行,可有效应用于该过程的工艺参数优化,同时此方法也为中药复方制剂提取工艺的优选提供一种新思路。 |
| 关键词: 参莲草 AHP-CRITIC法 Box-Behnken响应面设计 BP神经网络 遗传算法 |
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| Optimization of ShengLian Cao extraction process based on AHP-CRITIC method combined with BP neural network-genetic algorithm |
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lichunyu1, Liuweipeng1, zhengaizhu2, Qiuzhidong1, shiyuwen1, jiangmengcheng1, lina1, Jia Ailing1
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1.College of Pharmacy, Changchun University of Chinese Medicine, Changchun 130117, China;2.The Third Affiliated Hospital of Changchun University of Traditional Chinese Medicine
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| Abstract: |
| ABSTRACT: OBJECTIVE Using BP neural network-genetic algorithm combined with AHP-CRTIC method to optimize the extraction process of ShengLian Cao. METHODS Selecting deacetylasperulosidic acid methyl ester, Scutellarin, and paste rate as indicators, the mixed weight coefficients of each indicator were determined by the AHP-CRITIC method, and based on the Box-Behnken response surface experimental design, optimizing water addition times, extraction time and number of extractions in the extraction process of ShengLian Cao by BP neural network-genetic algorithm, to determine the optimal extraction process, and the optimization results were process validated. Results The optimized results of BP neural network-genetic algorithm were 8 times of water addition, 1.5 h of decoction time and 2 times of decoction, and the validation test showed that the overall score was 93.24. Conclusion The extraction process of ShengLian Cao based on the BP neural network-genetic algorithm is stable and feasible. At the same time, this method also provides a new idea for the optimization of the extraction process of traditional Chinese medicine compound preparation. |
| Key words: Shenglian cao AHP-CRITIC method Box-Behnken response surface design BP neural network genetic algorithm |
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