多输入麻醉控制系统的数据融合
|
摘要
随着社会不断发展进步,当代人类关心的问题不仅仅是生存,更多的是高质量的生活。医学的进步为人们追求这一目标提供了客观条件。外科手术,在人们生活中经常扮演着救死扶伤的角色。外科麻醉技术作为减轻人们痛苦,方便手术进程的重要手段,在外科手术当中是必不可少的。多年以来,各大医院所使用的麻醉技术多为人工手动麻醉,对于医生经验和技术要求很高,客观条件要求实现自动麻醉技术。为了更方便的进行自动麻醉,本课题提出了以多输入变量为测量变量,通过观测病人的生理特征,对整个麻醉过程实现基于数据融合的闭环自动控制。论文详细阐述了麻醉深度和监测手段,介绍了麻醉机的原理,结构和发展趋势,然后详述定量吸入麻醉理论和实践,以及如何使用数据挖掘技术进行数据的预处理,如何使用聚类方法进行数据融合。
论文提出了以输入的多数据融合为手段,解决不同输入变量对麻醉深度的影响问题。数据融合充分利用多数据中的冗余和互补信息,最大限度地估计出被测对象的真实参数。同时,数据融合大大方便了控制算法和控制器的设计,为系统简化提供了可行依据。
最后对于基于数据融合的麻醉自动控制系统的前景和目标做出总结和回顾。这种技术是对以往基于人工经验的麻醉技术的改进,节约了人力,提高了麻醉效率,避免了资源浪费,缩短了手术时间,进而保障手术的顺利进行。虽然项目的研究多在理论层面,但是其应用价值也是很乐观的。非常期待麻醉自动控制系统能够彻底取代手工麻醉的一天。
With the development of society, human beings nowadays concern about not only how to survive but also how to increase life quality. The development of medical science provides enough objective tools to pursue the goal. Surgeon aims to help those in need. The surgery anesthetic technology, as a method to alleviate people’s pain and accelerate the process of surgery, plays an essential role in surgery. Until now, most hospitals use the technology of human anesthetic, and this process requires experienced and skilled doctors. So this situation demands the realization of automatic anesthetic technology. In order to make the process more convenient, this thesis offers the idea of using multiple inputs as variables, to analyze the physical features of patience, and finally achieve the goal of closed-loop automatic control based on data fusion.
The thesis gives the detailed information about the anesthetic depth and monitoring methods, illustrates the basic principle of anesthetic machines--its structure and developing trend, then talks about the theory of quantitative anaesthesia and its realization, shows the ways of using data mining technology to preprocess data, specifies the how to utilize the clustering method to fuse data.
The thesis provides the method of using multiple inputs fusion to solve the problem of measuring influences of different variables to anesthetic depth. Data fusion utilizes the information of redundancies and compensations to evaluate the actual parameters of controlled objectives to the greatest extent. In the meantime, data fusion makes the designing of controller and algorithms much convenient, and offers feasible conditions to simplicity of the system.
The thesis casts the vision forward and makes a summary of anesthetic control system based on data fusion in the end. This technique is advancement towards old system which based on human experience, saves a lot of human resources, enhances the effectiveness of anesthetic, avoids the waste of resources, compresses the surgery time length, and in the end, guarantee the smooth process of surgery. Although the research over the project is almost at the level of theory, but through carefully analyzing the application value, the vision of the project is optimistic. I am looking forward to the day when anesthetic control system could completely replace human anesthesia.
论文提出了以输入的多数据融合为手段,解决不同输入变量对麻醉深度的影响问题。数据融合充分利用多数据中的冗余和互补信息,最大限度地估计出被测对象的真实参数。同时,数据融合大大方便了控制算法和控制器的设计,为系统简化提供了可行依据。
最后对于基于数据融合的麻醉自动控制系统的前景和目标做出总结和回顾。这种技术是对以往基于人工经验的麻醉技术的改进,节约了人力,提高了麻醉效率,避免了资源浪费,缩短了手术时间,进而保障手术的顺利进行。虽然项目的研究多在理论层面,但是其应用价值也是很乐观的。非常期待麻醉自动控制系统能够彻底取代手工麻醉的一天。
With the development of society, human beings nowadays concern about not only how to survive but also how to increase life quality. The development of medical science provides enough objective tools to pursue the goal. Surgeon aims to help those in need. The surgery anesthetic technology, as a method to alleviate people’s pain and accelerate the process of surgery, plays an essential role in surgery. Until now, most hospitals use the technology of human anesthetic, and this process requires experienced and skilled doctors. So this situation demands the realization of automatic anesthetic technology. In order to make the process more convenient, this thesis offers the idea of using multiple inputs as variables, to analyze the physical features of patience, and finally achieve the goal of closed-loop automatic control based on data fusion.
The thesis gives the detailed information about the anesthetic depth and monitoring methods, illustrates the basic principle of anesthetic machines--its structure and developing trend, then talks about the theory of quantitative anaesthesia and its realization, shows the ways of using data mining technology to preprocess data, specifies the how to utilize the clustering method to fuse data.
The thesis provides the method of using multiple inputs fusion to solve the problem of measuring influences of different variables to anesthetic depth. Data fusion utilizes the information of redundancies and compensations to evaluate the actual parameters of controlled objectives to the greatest extent. In the meantime, data fusion makes the designing of controller and algorithms much convenient, and offers feasible conditions to simplicity of the system.
The thesis casts the vision forward and makes a summary of anesthetic control system based on data fusion in the end. This technique is advancement towards old system which based on human experience, saves a lot of human resources, enhances the effectiveness of anesthetic, avoids the waste of resources, compresses the surgery time length, and in the end, guarantee the smooth process of surgery. Although the research over the project is almost at the level of theory, but through carefully analyzing the application value, the vision of the project is optimistic. I am looking forward to the day when anesthetic control system could completely replace human anesthesia.
引文
[1] 高 斌,麻醉深度监测的进展,中华中西医杂志,2006
[2] 王多友,段文健,低流量麻醉与关闭法麻醉的临床应用,2007
[3] 俞卫锋,定量吸入麻醉的理论与实践,中国宁波麻醉网,2007
[4] 韦汉鹏,麻醉机设计原理及进展,电子设计信息网,2005
[5] 徐彬,潘爽,霍利平,基于动态不确定度评定的加权数据融合算法,电光与控制 2007 年第 14 卷第 5 期
[6] 李静,贾利民,数据融合综述
[7] 刘同明 等 编著,数据挖掘技术及其应用,国防工业出版社 (2001)
[8] 邵峰晶 等 编著,数据挖掘原理与算法,中国水利水电出版社 (2003)
[9] 王秋生,段世明,单闯,闭环控制麻醉给药用于全静脉麻醉的研究进展,《国外医学》麻醉学与复苏分册,2003 年第 24 卷第 2 期
[10] 陈杭,王选,陈新忠,葛霏光,基于 PID 闭环控制算法的麻醉靶控输注给药的研究,中国生物医学工程学报,2007.5
[11] 罗英,中西医麻醉学发展史比较,《甘肃中医》2005 年第 18 卷第 10期
[12] 庄心良,曾因明《现代麻醉学》,人民卫生出版社,2004,7,3(15),1872-1874
[13] 吴东宇,董为伟,脑电非线性分析在认知功能研究中的应用,中华神经科杂志,2003,36(5),335
[14] 吴东宇,贾宝森,尹岭,脑电非线性分析在麻醉深度监测中的应用,解放军医学杂志,2005,30(1),40
[15] 吴东宇,尹岭,贾宝森.麻醉过程中意识记忆变化的脑电非线性分析监测.解放军医学杂志,2005,30(6),531
[16] 陈勇,佘守章,闫焱等,BIS 和 AEPI 监测镇静深度的评价,临床医学杂志,2005,21(10),662-664
[17] 胡振涛,刘先省,一种实用的数据融合算法,自动化仪表第 26 卷第8 期
[18] 彭煜玮,彭智勇,空间数据融合技术的研究,计算机工程 2007 年18 期
[19] 褚舒娟,姚尚龙,脑电双频指数在麻醉深度监测中的研究进展,国外医学,麻醉学与复苏分册,2005,26(3),170
[20] 陈伯銮,《临床麻醉药理学》,北京,人民卫生出版社,2000.7
[21] 吴琦,吸入麻醉药闭环控制用药的可行性研究,[学位论文],山东,山东大学,2004
[22] 王树清等编著,工业过程控制工程,北京,化学工业出版社教材出版中心,2003 年,20-38
[23] 吴麒编著,自动控制原理,北京,清华大学出版社,1990 年,106-150
[24] 施仁,刘文江,郑辑光等,自动化仪表与过程控制,北京,电子工业出版社,2003 年,196-269
[25] 王云,岳云,孙永海等,异丙酚靶控输注镇静时记忆与 BIS 、AEPI和效应室药物浓度的关系,中华麻醉学杂志,2004,24(2),105-108
[26] 刘瑞芳,安氟醚闭环靶控麻醉复合硬膜外阻滞的临床研究,[学位论文],山东,山东大学,2004
[27] 康芳,BIS、AEP 用于全身麻醉深度监测临床价值评估,安徽医学,2007,28(3),275-276
[28] 黄道平编著,MATLAB 与控制系统的数字仿真及 CAD,北京,化学工业出版社教材出版中心,2004 年,117-124
[29] 徐薇莉,田作华编著,自动控制理论与设计,上海,上海交通大学出版社,2007 年,50-88
[30] 汪晋宽,于丁文,张健,自动化概论,北京,北京邮电大学出版社,2006 年,46-52
[31] 谢克明,侯宏仑,复杂系统的智能控制方法闭.太原理工大学学报,1998,29(6),568-576
[32] 谢克明,南建峰,基于模糊神经网络的辨识与控制技术的现状及展望,太原理工大学学报,1998, 29(1),8-12
[33] 蔡自兴编著,智能控制,北京,电子工业出版社,2004
[34] 王耀南,智能控制系统,长沙,湖南大学出版社,1996
[35] 邵惠鹤编著,工业过程高级控制,第二版,上海,上海交通大学出版社,2003 年
[36] 吴东宇,尹岭,贾宝森.麻醉过程中意识记忆变化的脑电非线性分析监测.解放军医学杂志,2005,30(6),531
[37] 王室端,麻醉深度监测与全麻管理,齐鲁医学杂志,2006,21(3),280-282
[38] 傅守勇,帅训军,孙丽等,麻醉机原理与发展趋势,医疗设备信息,2003,18(12),33-35
[39] 于昕,韩松,现代麻醉机的基本原理及新进展,中国医疗器械杂志,2003,27(1),44-46
[40] 刘俊杰等,现代麻醉学,人民卫生出版社,1999
[41] 于布为,理想麻醉状态与麻醉深度监测,现代临床医学生物工程学杂志,2006,12(4),305
[42] 施仁,刘文江,郑辑光等,自动化仪表与过程控制,北京,电子工业出版社,2003 年,264-267
[43] 李国勇,谢克明,人工智能原理与应用,北京,高等教育出版社,2004
[44] 李国勇编注,智能控制及其 MATLAB 实现,北京,电子工业出版社,194-230
[45] 夏江燕,景亮麻醉深度监测技术及其临床应用,东南大学学报(医学版),2003,22(6),421-424
[46] 范从源等,麻醉物理学,上海科学技术文献出版社,1997
[47] 郭丹,当今麻醉领域的新潮流—麻醉工作站,中国医疗器械杂志,2003,27(1),35-36
[48] 于布为,理想麻醉状态与麻醉深度监测,现代临床医学生物工程学杂志,2006,12(4),305-306
[49] 陈仲清,史誉吾,食管下段收缩性与麻醉深度,《国外医学》麻醉学与复苏分册,1989,5,308
[50] 吴东宇,贾宝森,尹岭,脑电非线性分析在麻醉深度监测中的应用,解放军医学杂志,2005,30(1),40
[51] 于布为,全麻本质的探讨,中国麻醉与镇痛杂志, 2002,2, 1-3
[52] 庄心良,曾因明《现代麻醉学》,人民卫生出版社,2004,7,3(15),1872-1874
[53] 吴东宇,董为伟,脑电非线性分析在认知功能研究中的应用,中华神经科杂志,2003,36(5),335
[54] Kearse LA, Manberg P, Chamoun N, etal. Bispectral analysis of the electroencephalogram correlates with patient movement to skin incision during propofol/nitrous oxide anesthesia, Anesthesiology,1994, 81,1365-1370
[55] PinskerMC, Anesthesia: a pragmatic construct, Anesth Analg, 1986, 65 819-820.
[56] Adrian W Gelb,Development of Anaesthesiology,第四军医大学学报2002 年第 23 卷第 15 期
[57] Moriter E, StruysM, SmetD etal, Closed-loop contorlleda dministration of propofol using bispectr alanalysis.Anaesthsia, 1998, 53 (8) ,749- 754
[58] Goldberger AL,West BJ,R igney DR.On a mechanism of cardiac electrical instability.J Biophys,1985:525-528
[59] Ramchurm SK,Baijnath D,Murry A.Lowdimensional chaotic behaviour in heart rate variability.Computers in Cardio logy,2000,27∶473
[60] Wong CA,Fragen RJ,Fitzgerald PC,etal,the assicuation between propofol-induced loss of consciousness and the SNAPindex.Anaesth Analg,2005,100-141
[61] Chernik DA,Gillings D,Laine H,etal.Validity and reliability of the observers assessment of alertness/sedation scale:study withintravenous midazolam.J Clin Psycol Pharmacol,1900,10:224
[62] Bauerle K,Greim CA,SchrothM,etal.Prediction of depth ofsedation and Anaesthesia by Narcotrend EEGmonitor.Br J Anaesth,2004,92(6):841-845
[63] Evans JM,Monitoring anesthesia,Clinic Anesthesiol,1984,2:243
[64] PRYS-ROBERTS,Anaesthesia:practical or impossible construct, Br J Anaesth,1987,59(11),1341-1345
[65] P.J.Antsaklis, Defining Intelligent Control-Report of Task Force on Intelligent Control, IEEE Control Systems Magazine, 1994, 14(3),58-66
[66] K.M.Passino, Bridging the Gap between Conventional and IntelligentControl. IEEE Control Systems Magazine, 1993, 13(2),12-18
[67] R.J.Marks, Intelligence: Computational Versus Artificial , IEEE Transon Neural Networks, 1993,4(1),737-739
[68] K.J.Astrom, Thomas J. Mcavoy Intelligent Control , Proc. Cont,1992,(3): 115-127
[69] Morris Driels,Linear Control Systems Engineering, 北京,清华大学出版社,2000 年,57-205
[70] Duane Hanselman,Bruce Littlefield,精通 Matlab 7,北京,清华大学出版社,2006 年,257-266
[71] Lerou GC, Dirksen R, Beneken KHH, etal, A system model for closed-circuit inhalation anesthesia and Computer Study,Anesthesiology,1991,75,230-237
[72] Glass P. S.,Bloom M.,Kearse L., etal, Bispectral analysis measures sedation and memory effects of propofol, midazolam, isoflurane and alfentanil in healthy volunteers, Anesthesiology, 1997, 86,836-847
[73] Andrea G, Marco RG, Christian W, etal, Multitasked closed-loopcontrol in anesthesia, IEEE engineering in medicine and biology, 2001,January/February,39-53
[74] Xindong Wu,Data mining: artificial intelligence in data analysis,Information Visualisation, 2002. Proceedings. Sixth International Conference on
[75] Smith, M.H.; Pedrycz, W.;Expanding the meaning of and applications for data mining,Systems, Man, and Cybernetics, 2000 IEEE International Conference on,Volume 3, 8-11 Oct. 2000 Page(s):1874 vol.3
[76] Junhua Hu; Yongmei Liu;Designing and Realization of Intelligent Data Mining System Based on Expert Knowledge,Management of Innovation and Technology, 2006 IEEE International Conference on,Volume 1, June 2006 Page(s):380 – 383
[77] Campos, M.M.; Stengard, P.J.; Milenova, B.L.;Data-centric automated data mining,Machine Learning and Applications, 2005. Proceedings. FourthInternational Conference on,15-17 Dec. 2005 Page(s):8 pp.
[78] Palacios, F.; Xiaoou Li; Rocha, L.E.;Data Mining based on CMAC Neural Networks,Electrical and Electronics Engineering, 2006 3rd International Conference on,Sept. 2006 Page(s):1 – 4
[79] Czejdo, B.; Morzy, M.; Wojciechowski, M.; Zakrzewicz, M.;Materialized views in data mining,Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on,2-6 Sept. 2002 Page(s):827 – 831
[80] Thuraisingham, B.;A primer for understanding and applying data mining,IT Professional,Volume 2, Issue 1, Jan.-Feb. 2000 Page(s):28 - 31
[2] 王多友,段文健,低流量麻醉与关闭法麻醉的临床应用,2007
[3] 俞卫锋,定量吸入麻醉的理论与实践,中国宁波麻醉网,2007
[4] 韦汉鹏,麻醉机设计原理及进展,电子设计信息网,2005
[5] 徐彬,潘爽,霍利平,基于动态不确定度评定的加权数据融合算法,电光与控制 2007 年第 14 卷第 5 期
[6] 李静,贾利民,数据融合综述
[7] 刘同明 等 编著,数据挖掘技术及其应用,国防工业出版社 (2001)
[8] 邵峰晶 等 编著,数据挖掘原理与算法,中国水利水电出版社 (2003)
[9] 王秋生,段世明,单闯,闭环控制麻醉给药用于全静脉麻醉的研究进展,《国外医学》麻醉学与复苏分册,2003 年第 24 卷第 2 期
[10] 陈杭,王选,陈新忠,葛霏光,基于 PID 闭环控制算法的麻醉靶控输注给药的研究,中国生物医学工程学报,2007.5
[11] 罗英,中西医麻醉学发展史比较,《甘肃中医》2005 年第 18 卷第 10期
[12] 庄心良,曾因明《现代麻醉学》,人民卫生出版社,2004,7,3(15),1872-1874
[13] 吴东宇,董为伟,脑电非线性分析在认知功能研究中的应用,中华神经科杂志,2003,36(5),335
[14] 吴东宇,贾宝森,尹岭,脑电非线性分析在麻醉深度监测中的应用,解放军医学杂志,2005,30(1),40
[15] 吴东宇,尹岭,贾宝森.麻醉过程中意识记忆变化的脑电非线性分析监测.解放军医学杂志,2005,30(6),531
[16] 陈勇,佘守章,闫焱等,BIS 和 AEPI 监测镇静深度的评价,临床医学杂志,2005,21(10),662-664
[17] 胡振涛,刘先省,一种实用的数据融合算法,自动化仪表第 26 卷第8 期
[18] 彭煜玮,彭智勇,空间数据融合技术的研究,计算机工程 2007 年18 期
[19] 褚舒娟,姚尚龙,脑电双频指数在麻醉深度监测中的研究进展,国外医学,麻醉学与复苏分册,2005,26(3),170
[20] 陈伯銮,《临床麻醉药理学》,北京,人民卫生出版社,2000.7
[21] 吴琦,吸入麻醉药闭环控制用药的可行性研究,[学位论文],山东,山东大学,2004
[22] 王树清等编著,工业过程控制工程,北京,化学工业出版社教材出版中心,2003 年,20-38
[23] 吴麒编著,自动控制原理,北京,清华大学出版社,1990 年,106-150
[24] 施仁,刘文江,郑辑光等,自动化仪表与过程控制,北京,电子工业出版社,2003 年,196-269
[25] 王云,岳云,孙永海等,异丙酚靶控输注镇静时记忆与 BIS 、AEPI和效应室药物浓度的关系,中华麻醉学杂志,2004,24(2),105-108
[26] 刘瑞芳,安氟醚闭环靶控麻醉复合硬膜外阻滞的临床研究,[学位论文],山东,山东大学,2004
[27] 康芳,BIS、AEP 用于全身麻醉深度监测临床价值评估,安徽医学,2007,28(3),275-276
[28] 黄道平编著,MATLAB 与控制系统的数字仿真及 CAD,北京,化学工业出版社教材出版中心,2004 年,117-124
[29] 徐薇莉,田作华编著,自动控制理论与设计,上海,上海交通大学出版社,2007 年,50-88
[30] 汪晋宽,于丁文,张健,自动化概论,北京,北京邮电大学出版社,2006 年,46-52
[31] 谢克明,侯宏仑,复杂系统的智能控制方法闭.太原理工大学学报,1998,29(6),568-576
[32] 谢克明,南建峰,基于模糊神经网络的辨识与控制技术的现状及展望,太原理工大学学报,1998, 29(1),8-12
[33] 蔡自兴编著,智能控制,北京,电子工业出版社,2004
[34] 王耀南,智能控制系统,长沙,湖南大学出版社,1996
[35] 邵惠鹤编著,工业过程高级控制,第二版,上海,上海交通大学出版社,2003 年
[36] 吴东宇,尹岭,贾宝森.麻醉过程中意识记忆变化的脑电非线性分析监测.解放军医学杂志,2005,30(6),531
[37] 王室端,麻醉深度监测与全麻管理,齐鲁医学杂志,2006,21(3),280-282
[38] 傅守勇,帅训军,孙丽等,麻醉机原理与发展趋势,医疗设备信息,2003,18(12),33-35
[39] 于昕,韩松,现代麻醉机的基本原理及新进展,中国医疗器械杂志,2003,27(1),44-46
[40] 刘俊杰等,现代麻醉学,人民卫生出版社,1999
[41] 于布为,理想麻醉状态与麻醉深度监测,现代临床医学生物工程学杂志,2006,12(4),305
[42] 施仁,刘文江,郑辑光等,自动化仪表与过程控制,北京,电子工业出版社,2003 年,264-267
[43] 李国勇,谢克明,人工智能原理与应用,北京,高等教育出版社,2004
[44] 李国勇编注,智能控制及其 MATLAB 实现,北京,电子工业出版社,194-230
[45] 夏江燕,景亮麻醉深度监测技术及其临床应用,东南大学学报(医学版),2003,22(6),421-424
[46] 范从源等,麻醉物理学,上海科学技术文献出版社,1997
[47] 郭丹,当今麻醉领域的新潮流—麻醉工作站,中国医疗器械杂志,2003,27(1),35-36
[48] 于布为,理想麻醉状态与麻醉深度监测,现代临床医学生物工程学杂志,2006,12(4),305-306
[49] 陈仲清,史誉吾,食管下段收缩性与麻醉深度,《国外医学》麻醉学与复苏分册,1989,5,308
[50] 吴东宇,贾宝森,尹岭,脑电非线性分析在麻醉深度监测中的应用,解放军医学杂志,2005,30(1),40
[51] 于布为,全麻本质的探讨,中国麻醉与镇痛杂志, 2002,2, 1-3
[52] 庄心良,曾因明《现代麻醉学》,人民卫生出版社,2004,7,3(15),1872-1874
[53] 吴东宇,董为伟,脑电非线性分析在认知功能研究中的应用,中华神经科杂志,2003,36(5),335
[54] Kearse LA, Manberg P, Chamoun N, etal. Bispectral analysis of the electroencephalogram correlates with patient movement to skin incision during propofol/nitrous oxide anesthesia, Anesthesiology,1994, 81,1365-1370
[55] PinskerMC, Anesthesia: a pragmatic construct, Anesth Analg, 1986, 65 819-820.
[56] Adrian W Gelb,Development of Anaesthesiology,第四军医大学学报2002 年第 23 卷第 15 期
[57] Moriter E, StruysM, SmetD etal, Closed-loop contorlleda dministration of propofol using bispectr alanalysis.Anaesthsia, 1998, 53 (8) ,749- 754
[58] Goldberger AL,West BJ,R igney DR.On a mechanism of cardiac electrical instability.J Biophys,1985:525-528
[59] Ramchurm SK,Baijnath D,Murry A.Lowdimensional chaotic behaviour in heart rate variability.Computers in Cardio logy,2000,27∶473
[60] Wong CA,Fragen RJ,Fitzgerald PC,etal,the assicuation between propofol-induced loss of consciousness and the SNAPindex.Anaesth Analg,2005,100-141
[61] Chernik DA,Gillings D,Laine H,etal.Validity and reliability of the observers assessment of alertness/sedation scale:study withintravenous midazolam.J Clin Psycol Pharmacol,1900,10:224
[62] Bauerle K,Greim CA,SchrothM,etal.Prediction of depth ofsedation and Anaesthesia by Narcotrend EEGmonitor.Br J Anaesth,2004,92(6):841-845
[63] Evans JM,Monitoring anesthesia,Clinic Anesthesiol,1984,2:243
[64] PRYS-ROBERTS,Anaesthesia:practical or impossible construct, Br J Anaesth,1987,59(11),1341-1345
[65] P.J.Antsaklis, Defining Intelligent Control-Report of Task Force on Intelligent Control, IEEE Control Systems Magazine, 1994, 14(3),58-66
[66] K.M.Passino, Bridging the Gap between Conventional and IntelligentControl. IEEE Control Systems Magazine, 1993, 13(2),12-18
[67] R.J.Marks, Intelligence: Computational Versus Artificial , IEEE Transon Neural Networks, 1993,4(1),737-739
[68] K.J.Astrom, Thomas J. Mcavoy Intelligent Control , Proc. Cont,1992,(3): 115-127
[69] Morris Driels,Linear Control Systems Engineering, 北京,清华大学出版社,2000 年,57-205
[70] Duane Hanselman,Bruce Littlefield,精通 Matlab 7,北京,清华大学出版社,2006 年,257-266
[71] Lerou GC, Dirksen R, Beneken KHH, etal, A system model for closed-circuit inhalation anesthesia and Computer Study,Anesthesiology,1991,75,230-237
[72] Glass P. S.,Bloom M.,Kearse L., etal, Bispectral analysis measures sedation and memory effects of propofol, midazolam, isoflurane and alfentanil in healthy volunteers, Anesthesiology, 1997, 86,836-847
[73] Andrea G, Marco RG, Christian W, etal, Multitasked closed-loopcontrol in anesthesia, IEEE engineering in medicine and biology, 2001,January/February,39-53
[74] Xindong Wu,Data mining: artificial intelligence in data analysis,Information Visualisation, 2002. Proceedings. Sixth International Conference on
[75] Smith, M.H.; Pedrycz, W.;Expanding the meaning of and applications for data mining,Systems, Man, and Cybernetics, 2000 IEEE International Conference on,Volume 3, 8-11 Oct. 2000 Page(s):1874 vol.3
[76] Junhua Hu; Yongmei Liu;Designing and Realization of Intelligent Data Mining System Based on Expert Knowledge,Management of Innovation and Technology, 2006 IEEE International Conference on,Volume 1, June 2006 Page(s):380 – 383
[77] Campos, M.M.; Stengard, P.J.; Milenova, B.L.;Data-centric automated data mining,Machine Learning and Applications, 2005. Proceedings. FourthInternational Conference on,15-17 Dec. 2005 Page(s):8 pp.
[78] Palacios, F.; Xiaoou Li; Rocha, L.E.;Data Mining based on CMAC Neural Networks,Electrical and Electronics Engineering, 2006 3rd International Conference on,Sept. 2006 Page(s):1 – 4
[79] Czejdo, B.; Morzy, M.; Wojciechowski, M.; Zakrzewicz, M.;Materialized views in data mining,Database and Expert Systems Applications, 2002. Proceedings. 13th International Workshop on,2-6 Sept. 2002 Page(s):827 – 831
[80] Thuraisingham, B.;A primer for understanding and applying data mining,IT Professional,Volume 2, Issue 1, Jan.-Feb. 2000 Page(s):28 - 31