This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time ...This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT （Nie-Tan） method that is one of the fastest and simplest defuzzification methods. Because the DC （direct current） servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA （field programmable gate array） module hardware which is one of the most used platforms in the industry. The results show that the E-KM （enhanced KM） algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.展开更多
Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of ...Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.展开更多
AIM:To evaluate the safety of four insulin titration algorithms in a homogeneous population of insulin-na ve type 2 diabetic patients.METHODS:We conducted a 24-wk,open,single-center study with 92 insulin-na ve type 2 ...AIM:To evaluate the safety of four insulin titration algorithms in a homogeneous population of insulin-na ve type 2 diabetic patients.METHODS:We conducted a 24-wk,open,single-center study with 92 insulin-na ve type 2 diabetes patients who failed treatment with one or two oral drugs.The patients were randomized to one of the four following algorithms:LANMET(n=26)and LANMET PLUS(n=22)algorithms,whose patients received a fixed initial insulin dose of 10 U,and DeGold(n=23)and DeGold PLUS(n=21)algorithms,whose patients’initial insulin dose was based on their body mass index(BMI).In addition,patients in the PLUS groups had their insulin titrated twice a week from 2 to 8 U.In the other two groups,the titration was also performed also twice a week,but in a fixed increments of 2 U.The target fasting glucose levels for both groups was 100 mg/dL.RESULTS:There was no significant difference in efficacy parameters.There was no significant difference when comparing moderate hypoglycemia events in algorithms starting with a 10 U fixed dose and algorithms based on BMI.However,there was a significant increase in moderate hypoglycemia events among the PLUS treated patients when the LANMET and DeGold algorithms were compared with the 2 fast-titration PLUS algorithms.We observed 12 hypoglycemia events in the first group,which corresponded to 0.94 events/patient per year,and we observed 42 events in the second group,which corresponded to 2.81 events/patient per year(P<0.037).No further significant differences were observed when other comparisons between the algorithms were carried out.CONCLUSION:Starting insulin glargine based on BMI is safe,but fast titration algorithms increase the risk of moderate hypoglycemia.展开更多
Advanced glycation end products(AGEs)are a complex and heterogencous group of compounds that have been implicated in diabetes related complfcations.Sk in autofluorescence was recently introduced as an altemative tool ...Advanced glycation end products(AGEs)are a complex and heterogencous group of compounds that have been implicated in diabetes related complfcations.Sk in autofluorescence was recently introduced as an altemative tool for skin AGEs accumulation assessment in diabetes.Sucossful optical diagnosis of diabetes requires a rapid and accurate classification algorithm.In order to improve the performance of noninvasive and optical diagnosis of type 2 diabetes,support vector machines(SVM)algorithm was implemented for the clasification of skin autofluorescence from diabetics and control subjects.Cross-validation and grid optimization methods were employed to calculate the optimal parameters that ma ximize classification accuracy.Classification model was set up according to the training set and then veri fied by the testing set.The results show that radical basis fiunction is the best choice in the four common kernels in SVM.Moreover,a diagnostic accuracy of 82.61%,a sensitivity of 69.57%,and a specificity of 95.65%for discriminating diabetics from control subjects were achieved using a mixed kemel function,which is based on liner kernel function and radical basis function.In comparison with fasting plasma glucose and HbAue test,the clasifcation method of skin autofuorescence spectrum based on SVM shows great potential in screening of diabetes.展开更多
Taking the advantage of the nearly 14 000 items of muhi-source, multi-dimension practical dataset of type 2 diabetes, and a series of data mining experiments are designed to seek for important type 2 diabetes risk fac...Taking the advantage of the nearly 14 000 items of muhi-source, multi-dimension practical dataset of type 2 diabetes, and a series of data mining experiments are designed to seek for important type 2 diabetes risk factors and their relationships with blood glucose. The valuable pathological knowledge includes, the deci- sion tree is almost identical with the list of clinical diabetic risk factors; 9 items important risk factors of type 2 diabetes were found, and the relationship between the main risk factors and the blood glucose, and the feature of critical value of the risk factors were given too in this paper. These valuable results are good to the cure and macro-control type 2 diabetes.展开更多
复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性...复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。展开更多
文摘This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT （Nie-Tan） method that is one of the fastest and simplest defuzzification methods. Because the DC （direct current） servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA （field programmable gate array） module hardware which is one of the most used platforms in the industry. The results show that the E-KM （enhanced KM） algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.
文摘Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.
文摘AIM:To evaluate the safety of four insulin titration algorithms in a homogeneous population of insulin-na ve type 2 diabetic patients.METHODS:We conducted a 24-wk,open,single-center study with 92 insulin-na ve type 2 diabetes patients who failed treatment with one or two oral drugs.The patients were randomized to one of the four following algorithms:LANMET(n=26)and LANMET PLUS(n=22)algorithms,whose patients received a fixed initial insulin dose of 10 U,and DeGold(n=23)and DeGold PLUS(n=21)algorithms,whose patients’initial insulin dose was based on their body mass index(BMI).In addition,patients in the PLUS groups had their insulin titrated twice a week from 2 to 8 U.In the other two groups,the titration was also performed also twice a week,but in a fixed increments of 2 U.The target fasting glucose levels for both groups was 100 mg/dL.RESULTS:There was no significant difference in efficacy parameters.There was no significant difference when comparing moderate hypoglycemia events in algorithms starting with a 10 U fixed dose and algorithms based on BMI.However,there was a significant increase in moderate hypoglycemia events among the PLUS treated patients when the LANMET and DeGold algorithms were compared with the 2 fast-titration PLUS algorithms.We observed 12 hypoglycemia events in the first group,which corresponded to 0.94 events/patient per year,and we observed 42 events in the second group,which corresponded to 2.81 events/patient per year(P<0.037).No further significant differences were observed when other comparisons between the algorithms were carried out.CONCLUSION:Starting insulin glargine based on BMI is safe,but fast titration algorithms increase the risk of moderate hypoglycemia.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(083RC11124).
文摘Advanced glycation end products(AGEs)are a complex and heterogencous group of compounds that have been implicated in diabetes related complfcations.Sk in autofluorescence was recently introduced as an altemative tool for skin AGEs accumulation assessment in diabetes.Sucossful optical diagnosis of diabetes requires a rapid and accurate classification algorithm.In order to improve the performance of noninvasive and optical diagnosis of type 2 diabetes,support vector machines(SVM)algorithm was implemented for the clasification of skin autofluorescence from diabetics and control subjects.Cross-validation and grid optimization methods were employed to calculate the optimal parameters that ma ximize classification accuracy.Classification model was set up according to the training set and then veri fied by the testing set.The results show that radical basis fiunction is the best choice in the four common kernels in SVM.Moreover,a diagnostic accuracy of 82.61%,a sensitivity of 69.57%,and a specificity of 95.65%for discriminating diabetics from control subjects were achieved using a mixed kemel function,which is based on liner kernel function and radical basis function.In comparison with fasting plasma glucose and HbAue test,the clasifcation method of skin autofuorescence spectrum based on SVM shows great potential in screening of diabetes.
基金Sponsored by the National Natural Science Foundation of China(60671008)the National Science and Technology Support Project(2006038070031)the National"863"Program Project(2006AA02Z429)
文摘Taking the advantage of the nearly 14 000 items of muhi-source, multi-dimension practical dataset of type 2 diabetes, and a series of data mining experiments are designed to seek for important type 2 diabetes risk factors and their relationships with blood glucose. The valuable pathological knowledge includes, the deci- sion tree is almost identical with the list of clinical diabetic risk factors; 9 items important risk factors of type 2 diabetes were found, and the relationship between the main risk factors and the blood glucose, and the feature of critical value of the risk factors were given too in this paper. These valuable results are good to the cure and macro-control type 2 diabetes.
文摘复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。
