基于Grubbs规则和MATLAB语言快速剔除异常值方法的建立及其在药物苦度评价中的应用
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摘要
目的:建立基于Grubbs规则和MATLAB语言的异常值剔除方法,并评价其在药物苦度评价中的的应用效果。方法:以Grubbs规则为参考,建立基于MATLAB语言的异常值自动循环剔除方法。选择20名志愿者分别进行单组口尝试验(通草)和多组口尝试验(通草、明党参、茯苓等10种药材);选择7个传感器进行电子舌测试(川木通)。以上述试验所得的苦度评价数据(口尝试验为苦度值,电子舌测试为传感器响应值)为数据源,选择5名研究者,采用基于Grubbs规则的查表逐一剔除法(方法一)、基于Grubbs规则的Excel软件剔除法(方法二)、基于Grubbs规则和MATLAB语言的异常值自动循环剔除法(方法三)进行异常值的判定及剔除;以异常值剔除时间和错误概率为指标,评价上述3种方法的应用效果。结果:单组口尝试验苦度评价数据中有2个异常值,3种方法的剔除时间分别为(745.400 0±25.904 4)、(288.333 3±31.253 1)、(0.000 3±0.000 0)s,错误概率分别为20.0%、0、0;多组口尝试验苦度评价数据中有6个异常值,3种方法的剔除时间分别为(3 693.107 7±75.023 3)、(1 494.761 4±53.826 9)、(0.005 2±0.000 0)s,错误概率分别为10.0%、4.0%、0;电子舌测试苦度评价数据中有3个异常值,3种方法的剔除时间分别为(2 992.673 3±84.117 6)、(1 276.367 1±55.024 5)、(0.002 3±0.000 0)s,错误概率分别为5.7%、2.9%、0。3种方法的剔除结果一致;方法二的剔除时间显著短于方法一(P<0.01),方法三的剔除时间显著短于方法一和方法二(P<0.01);3种方法错误概率无显著差异(P>0.05)。结论:基于Grubbs规则和MATLAB语言的异常值自动循环剔除法可显著缩短苦度评价数据异常值的剔除时间,提高数据处理效率,可用于药物苦度评价。
OBJECTIVE:To establish the elimination method of outliers based on Grubbs rule and MATLAB language,and to evaluate the effects of it on drug bitterness evaluation. METHODS:Referring to Grubbs rule,the automatic cyclic outliers elimination method based on MATLAB language was established. Totally 20 volunteers were included in single oral taste test(Tetrapanax papyrifer)and multiple oral taste test(10 kinds of medicinal material as T. papyrifer,Changium smyrnioides,Poria cocos,etc.). Seven sensors were selected for electronic tongue test(Clematis armandii). The data of bitterness evaluation in above tests(oral taste test as bitterness value, electronic tongue test as response value of sensors)were used as the data source. Five researchers were selected and adopted table-by-table elimination method based on Grubbs rule(method one),Excel software elimination method based on Grubbs rule(method two) and automatic cyclic outliers elimination method based on Grubbs rule and MATLAB language(method three)to judge and eliminate the outliers. The effects of above three methods were evaluated with the removal time and error rate of outliers as indexes. RESULTS:There were two outliers in the data of bitterness evaluation in single oral taste test;the elimination time of the three methods were(745.400 0 ± 25.904 4),(288.333 3 ± 31.253 1)and(0.000 3 ± 0.000 0)s,respectively;error rates were 20.0%,0 and 0,respectively. There were six outliers in the data of bitterness evaluation in multiple oral taste test;the elimination time of three methods were(3 693.107 7±75.023 3),(1 494.761 4±53.826 9),(0.005 2±0.000 0)s,respectively;error rates were 10.0%,4.0%,0,respectively. There were three outliers in the data of bitterness evaluation in electronic tongue test;the elimination time of three methods were(2 992.673 3±84.117 6),(1 276.367 1±55.024 5),(0.002 3±0.000 0)s,respectively;error rates were 5.7%,2.9%,0,respectively. The elimination results of the three methods were consistent. The elimination time of method two was significantly shorter than that of method one(P<0.01);the elimination time of method three was significantly shorter than those of method one and method two(P<0.01). There was no significant difference in error rate of 3 methods(P>0.05). CONCLUSIONS:The automatic cyclic elimination method of outliers based on Grubbs rule and MATLAB language can significantly shorten the elimination time of outliers in data of drug bitterness evaluation,improve the efficiency of data processing,and is suitable for drug bitterness evaluation.
OBJECTIVE:To establish the elimination method of outliers based on Grubbs rule and MATLAB language,and to evaluate the effects of it on drug bitterness evaluation. METHODS:Referring to Grubbs rule,the automatic cyclic outliers elimination method based on MATLAB language was established. Totally 20 volunteers were included in single oral taste test(Tetrapanax papyrifer)and multiple oral taste test(10 kinds of medicinal material as T. papyrifer,Changium smyrnioides,Poria cocos,etc.). Seven sensors were selected for electronic tongue test(Clematis armandii). The data of bitterness evaluation in above tests(oral taste test as bitterness value, electronic tongue test as response value of sensors)were used as the data source. Five researchers were selected and adopted table-by-table elimination method based on Grubbs rule(method one),Excel software elimination method based on Grubbs rule(method two) and automatic cyclic outliers elimination method based on Grubbs rule and MATLAB language(method three)to judge and eliminate the outliers. The effects of above three methods were evaluated with the removal time and error rate of outliers as indexes. RESULTS:There were two outliers in the data of bitterness evaluation in single oral taste test;the elimination time of the three methods were(745.400 0 ± 25.904 4),(288.333 3 ± 31.253 1)and(0.000 3 ± 0.000 0)s,respectively;error rates were 20.0%,0 and 0,respectively. There were six outliers in the data of bitterness evaluation in multiple oral taste test;the elimination time of three methods were(3 693.107 7±75.023 3),(1 494.761 4±53.826 9),(0.005 2±0.000 0)s,respectively;error rates were 10.0%,4.0%,0,respectively. There were three outliers in the data of bitterness evaluation in electronic tongue test;the elimination time of three methods were(2 992.673 3±84.117 6),(1 276.367 1±55.024 5),(0.002 3±0.000 0)s,respectively;error rates were 5.7%,2.9%,0,respectively. The elimination results of the three methods were consistent. The elimination time of method two was significantly shorter than that of method one(P<0.01);the elimination time of method three was significantly shorter than those of method one and method two(P<0.01). There was no significant difference in error rate of 3 methods(P>0.05). CONCLUSIONS:The automatic cyclic elimination method of outliers based on Grubbs rule and MATLAB language can significantly shorten the elimination time of outliers in data of drug bitterness evaluation,improve the efficiency of data processing,and is suitable for drug bitterness evaluation.
引文
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[15]刘瑞新,李慧玲,李学林,等.基于电子舌的穿心莲水煎液的掩味效果评价研究[J].中草药,2013,44(16):2240-2245.
[16]李学林,王盼盼,刘瑞新,等.3种掩味剂单独或联合应用对黄柏的掩味作用探究及掩味前后化学成分的比较[J].中国实验方剂学杂志,2017,23(2):7-11.
[17]王优杰,徐德生,冯怡.中药及其制剂苦味评价方法的建立[J].中国中药杂志,2007,32(15):1511-1514.
[18]LIU R,ZHANG X,ZHAGN L,et al.Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network[J].Exp Ther Med,2014,7(6):1696-1702.
[19]周中汉,王汉江,李梅,等.利用DPS剔除测量数据中的异常值[J].计量技术,2007(10):61-63.
[20]国家药典委员会.中华人民共和国药典:一部[S].2015年版.北京:中国医药科技出版社,2015:210.
[2]LI L,NAINI V,AHMED SU.Utilization of a modified special-cubic design and an electronic tongue for bitterness masking formulation optimization[J].J Pharm Sci,2007,96(10):2723-2734.
[3]李学林,陈鹏举,桂新景,等.电子舌在羟丙基-β-环糊精抑苦规律研究中的应用[J].中草药,2017,48(20):4235-4244.
[4]LI X,GAO X,LIU R,et al.Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue[J].Exp Ther Med,2016,12(5):2949-2957.
[5]FIELD MS.Application of robust statistical methods to background tracer data characterized by outliers and left-censored data[J].Water Res,2011,45(10):3107-3118.
[6]BUCKLEY JA,GEORGIANNA TD.Analysis of statistical outliers with application to whole effluent toxicity testing[J].Water Environ Res,2001,73(5):575-583.
[7]中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T4883-2008数据的统计处理和解释:正态样本离群值的判断和处理[S].北京:中国标准出版社,2008:4-5.
[8]JAIN RB.A recursive version of Grubbs’test for detecting multiple outliers in environmental and chemical data[J].Clin Biochem,2010,43(12):1030-1033.
[9]GRAAFLAND H,SEIGNALET J,DONADIO D,et al.Our experince with antiglobulin consumption(Dixon test)in the study of antibodies bound to platelets[J].Rev Fr Transfus Immunohematol,1981,24(4):389-404.
[10]尹江丽,王琳静.兵器试验中的异常值检验[J].四川兵工学报,2013,34(6):137-139.
[11]中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T12315-1990感官分析方法学排序法[S].北京:中国标准出版社,2008:4-5.
[12]祝国强,杭国明,滕海英,等.谈谈两总体比较的非参数检验方法[J].数理医药学杂志,2011,24(5):524-525.
[13]刘瑞新,张杏芬,李学林,等.3种口尝评价方法用于药物苦度评价的比较[J].中国实验方剂学杂志,2013,19(20):118-122.
[14]李学林,吴子丹,刘瑞新,等.口尝法评价中药汤剂苦味的研究[J].中国实验方剂学杂志,2011,17(23):11-13.
[15]刘瑞新,李慧玲,李学林,等.基于电子舌的穿心莲水煎液的掩味效果评价研究[J].中草药,2013,44(16):2240-2245.
[16]李学林,王盼盼,刘瑞新,等.3种掩味剂单独或联合应用对黄柏的掩味作用探究及掩味前后化学成分的比较[J].中国实验方剂学杂志,2017,23(2):7-11.
[17]王优杰,徐德生,冯怡.中药及其制剂苦味评价方法的建立[J].中国中药杂志,2007,32(15):1511-1514.
[18]LIU R,ZHANG X,ZHAGN L,et al.Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network[J].Exp Ther Med,2014,7(6):1696-1702.
[19]周中汉,王汉江,李梅,等.利用DPS剔除测量数据中的异常值[J].计量技术,2007(10):61-63.
[20]国家药典委员会.中华人民共和国药典:一部[S].2015年版.北京:中国医药科技出版社,2015:210.