
王熙弱胜能照,男,1963年生,教授,博士生导师。现任河北大学数学与计算机学院院长,河北省机器学来自习与计算智能重点实验室主任。
- 中文名称 王熙照
- 外文名称 Wang Xizhao
- 国籍 中国
- 民族 汉族
- 出生日期 1963年
个人简介
王熙照,博士,教授,博士来自生导师,IEEE Fellow,20养钟位田村13年H因子为18。
她势创注于照好绝形批独1998年毕业于哈尔滨工业大学计算机系,获工学博士学位(计算机应用专业);1998年至2001年赴香港理工大学计算学系合作研究,任研究员(Research Fellow);2000年10月至今任河北大学数学与计算机学院院长360百科,2007年至今任河北省机器学习与计算智能重点实验室主任。
主要研究方向为机器学习环东严路翻质治院鲁之与不确定性信息处理,包括示例模糊表示的归纳学习、近似推理与专家系统、神经网络敏感性分析、统计学习理论与支撑六附祖觉肉印然统向量机、模糊测度与模糊积分、粗糙集、极速学习机(Extreme Learning Machine, ELM)和大数据机器学习理论与方法等。至今,共出版学术专著3部,教材2部;在IEEE Transactions on PAMI包木余那充、Information Sc架爱课者早也飞代iences等杂志和会议发表学术论文150多篇,其中SCI、EI检索100余篇;Google Scholar 搜索显示论文累计引用次数超过2000次,单篇最高引素植错知用超过200次。H因子2013年4月查询为18。主持国家自然科学基金项目、教育部科学技术研究重点项目、国家发改委基金项目及河北省自然科学基金项目等20余项;获河北省自然科学一等奖1项,毛放评理教育部高等学校科学技术奖自效左西老攻者粉展费批福然科学二等奖1项,河北省自然科学三等奖2项,河北省科技进步三等奖1项;2007年入选河北省教育厅首批全百名优秀创新人才支持计划,2009年获全国模范教师称号。
王熙照教授是IE班副胡些流理队手圆EESMCS董事局成员和IEEESMC计算智能专业委员会主席。2002-2012连续11年作为会议主席主持召开了由IEEESMC联合主办的第1至第11届机器学习与控制论国际会议(ICMLC02-12)。鉴于为IEEESMC协会作出的突出贡献,王熙照教授获得IEEESMC急协会的多个奖项。
王熙照教食投土住授由于在模糊决策树和聚类技术领域做出的突出贡献于2012年当选为IEEE Fellow.
教育经历
1979.09-1983.06 河北大学数学系学习
1983.07 河北大学数学系获理学学士学位(数学专业)
198北站演5.09-1987.07 上海交通大学应用数学系研究生班学习
1990.02 河北大学数学系获理学硕士学位(基础数学专业)
1995.09-1996.07 哈尔滨工业大学计算绿老须温鲜色形买跑映房机科学与工程系学习博士学位课程
1998.09 哈尔滨工业大学计算机科学与工程系获工学博士若学位(计算机应用专业)
工作经历
1983.07-1988.01 助教,河北大学数学系
1988.02-1993.06 讲师,河北大学数学系
1993.07-1998.10 副教授,河北大学数学系,应用数学教研室主任
1998.11-2013.05 教授来自,河北大学数学与计算史高灯常露别日机学院
1998.09-2001.09 研究员社互就亮试停乐存通木(Research Fel给别low),香港理工大学计算科学系
2000.10-20360百科13.05 教授/博导,河北大学数学与计算机学院院长
学术兼职
IEEE Fellow;IEEE-SMC董事局成员(2005, 2007-2009, 2012-2014);
IEEE-SMC计算智能技术委员会主席;
IEEE SMC Baoding Chapter 主席;
国际杂志Machine Learning and Cybernetics主编;
国际杂志IEEE Transactions on SMC Part(B) 副主编;
国际杂志Information Science 副主编;
国际杂志Pattern R又仅称ecognition and Artificial Intelligence副主编;
第六届中国工业与应用数微车五地县帮完到航学学会理事;
第五届、第六届中国人工智能学会理事;
中国人工智能座学会第六届知识工程专业委员会肉呢需析密支般差承作侵副主任委员;
中国人工智能学会第五场料届、第六届机器学习专业委员会常务委员 ;
中国人工智能学会第二届、第三届粗糙集与软计算专业委员应西阻会常务委员;
第一届、第二届河北省机器学习学会理事长 ;
第三届河重耐亚证北省工业与应用数学学会副理事长;
河北省人工智能学会副理事长;
河北省数学建模组委会主任;
《模糊系统与数学》杂志编委
科研项目
28) 2013.01-2015.12 (主持) 河北省自然修德占担础科学基金项目:主动学习中的不确刚求这急除哥定性及其应用研究 (项目编态临走编美号:F2013201110,RMB50,000)
27) 2012.01-2015.12 (主持) 国家自然科学基金项目:归纳学习中的不确定性研究 (项目编号:61170040,R控肥罪急父船药MB560,000)
26) 2010.01-2012.12 (主持) 河北省教育厅重点项目:基于不确定约简的海量数据挖掘 (项目编号:ZD2010139,RMB50,000)
25) 2008.01-2010.12 (主持) 河北省应用基础研究重点项目:异常点挖掘研究及其应用 (项目编号:08963522D,RMB100,000)
24) 2008.01-2010.12 (主持) 岩河北省自然科学基金项目:基于最大Margin的决策树归纳学习系统及在操殖多光谱数据分类中的应用 (项目编号:F2008000635, RMB50,000)
23) 2007.01-2009.12 (主持) 河北省教育厅首批百名优秀创新人才支持计划 (RMB200,000)
22) 2005.目曾换做华聚苦小还09-2008.09 (主研) 国家自然科学基金项目:基于不确定信息的确统计学习理论 (项目编号:60573069, RMB200,0谁定听呀德互罗离续水00)
21) 2005.01-2007.12 (主持) 国家自然科学基金项目:加权模糊规则泛化的能力研究 (项目编号:60473045,RMB180,000,结题为优)
20) 2004.08-2006.12 (参加) 香港RGC基金资助项目:基于模糊粗糙集的模糊规则抽取与模糊属性约减
19) 2004.01-2006.12 (主持) 国家发展改革委员会项目:电力智能服务系统 (项目编号:2003-1954,RMB1,200,000)
18) 2003.01-2005.12 (主持) 河北省教育厅博士基金:模糊神经网络研究及其在规则学习中的应用 (项目编号:B2003117,RMB40,000)
17) 2003.01-2005.12 (主持) 教育部科学技术研究重点项目:带有互动因子的模糊推理研究(项目编号:03017,RMB50,000,2007年获教育部高等学校科学技术奖自然科学二等奖)
16) 2002.01-2004.12(主持)河北省教育厅基金项目:模糊推理中的交互影响研究(项目编号:2002159,RMB15,000,2007年获河北省自然科学三等奖)
15) 2003.01-2005.12 (主持) 河北省自然科学基金项目:模糊值属性特征子集的选取(项目编号:603137,RMB100,000,2007年获河北省自然科学一等奖)
14) 2002.01-2004.12(主研)河北省教育厅基金项目:Internet上用户访问信息的挖掘及应用(项目编号:2001206,RMB10,000,2007年河北省科技进步三等奖)
13) 2002.01-2003.12 (主持) 河北省教育厅基金项目:中文文本挖掘及其应用研究 (项目编号:2002154,RMB10,000)
12) 2001.01-2002.12 (主持) 河北大学博士基金资助项目:基于模糊积分的神经网络融合 (RMB25,000)
11) 1998.09-2001.09 (Research Fellow) 项目标题:模糊值特征子集的最优选取,RGC基金资助 (项目编号:G-T209,资助基金:港币200,000元,项目申请者:Eric Tsang博士)
10) 1998.09-2001.09 (Research Fellow) 项目标题:基于相似性的带有交互影响的模糊推理,RGC基金资助 (项目编号:G-T210,资助基金:港币200,000元,项目申请者:Daniel Yeung教授)
9) 1998.09-2001.09 (Research Fellow) 项目标题:结合基于案例的推理和模糊规则归纳于系统维护,RGC基金资助 (项目编号:G-V957,资助基金:港币429,880元,项目申请者:Simon Shiu博士)
8) 1998.09-2001.09 (Research Fellow) 项目标题:学习特征权-基于案例的推理系统的维护方法,RGC基金资助 (项目编号:A-PA88,资助基金:港币180,000元,项目申请者:Eric Tsang博士)
7) 1998.09-2001.09 (Research Fellow) 项目标题:基于案例的模糊专家系统的校验,计算机系研究基金资助 (项目编号:PA25,资助基金:港币150,000元,项目申请者:Simon Shiu 博士)
6) 1998.09-2001.09 (Research Fellow) 项目标题:模糊技术在智能混合系统中的应用,香港理工大学合作研究基金资助 (项目编号:G-YY12,资助基金:港币1,194,000元,项目申请者:香港理工大学计算科学系杨苏教授)
5) 1998.01-2000.12 (主持) 河北省自然科学基金资助项目:基于模糊信息的示例学习理论和算法 (项目编号:698139, RMB40,000,2003年获河北省自然科学三等奖)
4) 1997.06-1998.05 (主持) 辽河油田勘探开发研究院课题:雷14-20井区储层横向预测 (项目编号:雷14-20, RMB120,000)
3) 1997.01-1999.12 (参加) 河北省自然科学基金资助项目:模糊控制理论及其应用 (项目编号:97543306D, RMB40,000)
2) 1991.01-1993.06 (参加) 河北省自然科学基金资助项目:不精确信息的定量表示与不确定性数据库理论 (1994年获省教委科技进步2等奖)
1) 1989.01-1992.01 (参加) 国家自然科学基金资助项目:模糊信息处理的数学基础 (1993年获河北省教委科技进步2等奖)
获奖情况
12)IEEE-SMC最活跃SMC技术委员会奖,2009IEEE Outstanding Committee on Computational Intelligence, Received in the IEEEInternational Conference on Systems, Man & Cybernetics, October 11-14,2009, Hyatt Regency River-walk, San Antonio, Texas, USA
11)IEEE-SMC杰出Chapter奖,2008 IEEE Outstanding SMCs ChapterAward, Accepted in the IEEE International Conference on Systems, Man &Cybernetics, October 12-15, 2008,Singapore, International Convention andExhibition Centre
10)河北省自然科学1等奖,第1完成人,(河北省自然科学基金项目:模糊值属性特征子集的选取),2007
9) 教育部高等学校科学技术奖自然科学2等奖,第4完成人,(项目名称:复杂不确定环境下软计算技术及其应用),2007
8) 河北省自然科学3等奖,第1完成人,(教育部科学技术研究重点项目和教育厅项目:带有交互作用的模糊分类和模糊推理研究) ,2007
7) 河北省科技进步3等奖,第2完成人,(河北省教育厅项目:Internet上用户访问信息与中文文本信息的挖掘及应用) ,2007
6) IEEETransactions on SMC Part B最佳副主编奖,2006 IEEE SMC Best Associate Editor Award, Accepted in the IEEEInternational Conference on Systems, Man & Cybernetics, October 8-11, 2006,Taipei, Taiwan, CHINA
5) IEEE-SMC杰出贡献奖,2004 IEEE SMC OutstandingContribution Award, Accepted in the IEEE International Conference on Systems,Man Cybernetics, October 12-15, 2004, Netherlands Congress Center, The Hague,HOLLAND
4) 河北省自然科学3等奖,第1完成人,(河北省自然科学基金项目: 基于模糊信息的示例学习理论和算法),2003
3) 黑龙江省科技进步1等奖,第8完成人,(项目名称:农业专家系统及其开发工具研究) ,2002
2) 河北省教委科技进步2等奖,第3完成人,(河北省自然科学基金资助项目: 不精确信息的定量表示与不确定性数据库理论),1994
1) 河北省教委科技进步2等奖,第2完成人,(国家自然科学基金资助项目: 模糊信息处理的数学基础),1993
学术交流
38)第三届极速学习机国际研讨会,2012年12月11日-13日,新加坡
37)IEEE InternationalConference on Systems, Man & Cybernetics,2012年10月9日-12日,韩国
36)International Conference onMachine Learning and Cybernetics,2012年7月15日-17日,西安
35)第二届极速学习机国际研讨会,2011年12月6日-8日,杭州
34)International Conference onMachine Learning and Cybernetics,2011年7月10日-13日,桂林
33)第一届极速学习机国际研讨会,2010年12月7日,澳大利亚
32)IEEE InternationalConference on Systems, Man & Cybernetics,2010年10月10日-13日,土耳其
31)International Conference onMachine Learning and Cybernetics,2010年7月11日-14日,青岛
30)中国数据挖掘会议,2010年5月6日-9日,广州
29)International Conference onRough Sets, Fuzzy sets, Data mining and Granular Computer,2009年12月18-23日,印度理工大学,新德里
28)IEEE InternationalConference on Systems, Man & Cybernetics,2009年10月11日-14日,美国
27)International Conference onMachine Learning and Cybernetics,2009年7月12日-15日,保定
26)第14届中国模糊系统与模糊数学大会,2008年10月31日-11月3日,武夷山
25)IEEE InternationalConference on Systems, Man & Cybernetics,2008年10月12日-15日,新加坡
24)International Conference onMachine Learning and Cybernetics,2008年7月12日-15日,昆明
23)IEEE InternationalConference on Systems, Man & Cybernetics,2007年10月7日-10日,加拿大
22)International Conference onMachine Learning and Cybernetics,2007年8月20日-23日,香港
21)第10届中国机器学习学术会议,2006年10月13日-15日,海口
20)International Conference onMachine Learning and Cybernetics,2006年8月13日-16日,大连
19)Asia-Pacific Workshop onVisual Information Processing,2005年12月11日-13日,香港
18)中国人工智能学会第11届全国学术年会,2005年10月31日-11月2日,武汉
17)IEEE InternationalConference on Systems, Man & Cybernetics,2005年10月10日-12日,美国
16)International Conference onMachine Learning and Cybernetics,2005年8月19日-21日,广州
15)IFSA World Congress,2005年7月28日-31日,北京
14)IEEE InternationalConference on Systems, Man & Cybernetics,2004年10月12日-15日,荷兰
13)International Conference onMachine Learning and Cybernetics,2004 年8月26日-29日,上海
12)中国人工智能学会第10届全国学术年会,2003年11月,广州
11)International Conference onMachine Learning and Cybernetics,2003年11月2日-5日,西安
10)中国人工智能学会机器学习8届学术会,2002年12月,广州
9) International Conferenceon Machine Learning and Cybernetics,2002年11月4日-5日,北京
8) Joint 9th IFSA WorldCongress and 20th NAFIPS International Conference,2001年7月25日-28日,加拿大
7) IEEE InternationalConference on Systems, Man & Cybernetics,2000年10月8日-11日,美国
6) IEEE InternationalConference on Systems, Man & Cybernetics,1999年10月12日-15日,日本
5)中国模糊数学与模糊系统委员会第9届年会,1998年8月,保定
4)中国模糊数学与模糊系统委员会第7届年会,1994年8月,太原
3)中国模糊数学与模糊系统委员会第6届年会,1992年8月,黄山
2) Sino-Japan Joint Meetingon Advanced Fuzzy Sets and Systems,1990年,北京
1)中国模糊数学与模糊系统委员会第5届年会,1990年8月,成都
大会报告/特约报告
26)2013年4月28日,哈尔滨工业大学深圳研究生院,深圳,报告题目:New Advances in Architecture Selection of Random Weight Networks
25)2012年12月21日,香港城市大学,香港,报告题目:Architecture Selection ofELMs and Their Improved Training Algorithms
24)2012年12月12日,2012 InternationalSymposium on Extreme Learning Machines,新加坡,报告题目:Architecture Selection of ELMs and Their ImprovedTraining Algorithms
23)2012年12月9日,马来西亚科技大学,马来西亚,报告题目:Architecture Selection ofRWNs and Their Improved Training Algorithms
22)2012年11月28日,Swinburne University,墨尔本,澳大利亚,报告题目:Architecture Selection ofELMs and Their Improved Training Algorithms
21)2012年11月27日,The 1st Computer Science Workshop in La TrobeUniversity,墨尔本,澳大利亚,报告题目:Architecture Selection ofELMs and Their Improved Training Algorithms
20)2012年10月14-17日,韩国首尔,参加IEEE-SMC年会、董事会并作大会主题报告
19)2012年9月29日,广州工业大学,广州,报告题目:Handling Uncertainty inSupervised Learning
18)2012年4月28日,华南理工大学,广州,报告题目:Handling Uncertainty inSupervised Learning
17)2012年4月25日,河南师范大学,新乡,报告题目:Uncertainty in ExtremeLearning Machine
16)2012年3月12日,苏州大学973项目研讨会议,苏州,报告题目:Intelligent InformationSystem and Learning in Uncertain Environments
15)2011年11月10日,IEEE-SMC Distinguished Lecture Program,香港城市大学,香港,报告题目:Handling Uncertainty inSupervised Learning
14)2011年11月2日,河北大学,保定,报告题目:Handling Uncertainty inSupervised Learning
13)2011年9月7日,IEEE-SMC Distinguished Lecture Program,香港理工大学,香港,报告题目:Different Writing: fromAcademic Papers to Research Proposals
12)2011年8月29日,中山大学,广州,报告题目:Handling Uncertainty inSupervised Learning
11)2011年8月26日,IEEE-SMC Distinguished Lecture Program,香港理工大学,香港,报告题目:Handling Uncertainty inSupervised Learning
10)2010年6月,新乡大学,新乡,报告题目:Inverse Problem of SupportVector Machines and Its Applications
9) 2009年8月,the 9th Conference of ChinaRough Set and Soft Computing,河北师范大学,石家庄,报告题目:A Comparative Study on RuleGeneration Between Decision-tree-based and Rough-set-based Approaches
8) 2009年5月10日,浙江海洋大学,舟山,报告题目:Sample Selection Based onMaximum Uncertainty
7) 2008年12月8日,IEEE-SMC Distinguished Lecture Program,台湾科技大学,台湾,报告题目:Sample Selection Based onMaximum Uncertainty
6) 2008年12月5日,2008 Workshop on Consumer Electronics,景文科技大学,台湾,报告题目:Fuzzy Integral and ItsApplication to Classification
5) 2008年10月31日,14届中国模糊数学与模糊系统会议,福建,报告题目:Fuzzy Integral and ItsApplication to Classification
4) 2008年9月22日,IEEE-SMC Distinguished Lecture Program,香港城市大学,香港,报告题目:Fuzzy Integral and ItsApplication to Classification
3) 2006年9月18日,2006 Asian Fuzzy Systems Society InternationalConference,保定,报告题目:Information Fusion based onFuzzy Integrals and Its Application to Classification
2) 2006年10月10日,13届中国模糊数学与模糊系统会议,陕西师范大学,西安,报告题目:Theoretical Foundations ofStatistical Learning Theory and Research on the Generalization of SVM
1) 2006年8月15日, International Conference on Machine Learning andCybernetics,大连,报告题目:SVM Inverse Problem and ItsApplication to Decision Tree Induction
学术服务
会议主席: ICMLC (International Conference on Machine Learning and Cybernetics) 2002-2013
ICWAPR (International Conference on Wavelet Analysis and Pattern Recognition) 2009-2013
评审主席: CYBCONF2013 (IEEE International Conference on Cybernetics)
组织主席: ELM2011 (The International Symposium on Extreme Learning Machines)
程序主席: 第十四届全国机器学习会议,2013
ELM2012-2013 (The International Conference on Extreme Learning Machines)
IEEESMC (IEEE International Conference on Systems, Man, and Cybernetics) 2008-2011
Easy-Chair Account (May 2013): 1. AI 11: PC member// 2. AMLTA2012: PC member// 3. CCML2013: chair// 4. CRSSC-CWI-CGrC 2013: PC member// 5. CRSSC-CWI-CGrC'2011: PC member// 6. DS 2013: PC member// 7. MLA 2013 Workshop: chair// 8. MLFD 2012: chair// 9. NCIIP2013: PC member// 10. RSFDGrC-2011: PC member// 11. SMC2010: track chair
学术简介
编辑专刊
[9] "Uncertainty in Learning from Big Data", Special Issue in Int. Journal of Fuzzy Sets and Systems, Elsevier Inc., Edited by Xi-zhao Wang, et al, 2013-2014 (in progress)
[8] "Uncertainty and Extreme Learning Machine", Special Issue in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific Publishing Co., Edited by Xi-zhao Wang, et al, 2013 (in progress).
[7] "Intelligent Web Information System and Learning in Uncertain Environments", Special Issue in Int. Journal of World Wide Web, Springer-Verlag, Edited by Xi-zhao Wang, Hui Wang, 2013 (in progress).
[6] "Extreme learning machine", Special Issue of Soft computing, Springer-Verlag, Edited by Xi-zhao Wang, Dianhui Wang, Guangbin Huang, 2011.
[5] "Soft Computing on Machine Learning and Cybernetics", Special Issue of Soft computing, Springer-Verlag, Edited by Witold Pedrycz, Daniel Yeung, Xi-zhao Wang, 2009.
[4] "Recent advance in granular computing", Special Issue of Information sciences, Elsevier Inc., Edited by Daniel, Yeung, Xi-zhao Wang, De-Gang Chen, 2008.
[3] "Learning with fuzzy representation and its application to pattern recognition", Special Issue of the International Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing Co., Edited by Xi-zhao Wang, Y. Y. Tang, Daniel Yeung, 2008.
[2] "Machine learning techniques: problems and applications", Special Issue of Soft computing, Springer-Verlag, Edited by Zhi-Qiang Liu, Daniel So Yeung, Xi-zhao Wang, Eric Tsang, 2005.
[1] "模糊集理论与应用", 中国模糊数学与模糊系统委员会第九届年会论文选集,刘应明、吴从忻、王熙照,1998年
专著教材
[5] 王熙照,翟俊海,基于不确定性的决策树归纳,科学出版社,2012年
[4] 王熙照,模糊测度和模糊积分及在分类技术中的应用,科学出版社,2008年
[3] 王熙照,哈明虎,模糊示例学习与模糊控制,河北大学出版社,2002年
[2] 王熙照,概率论与数理统计,科学出版社, 2009年
[1] 王熙照,陈昊,湛燕,"数据库原理及其应用",河北人民出版社,2005年
期刊论文
IEEE Transactions系列
[14] Xi-zhao Wang, Yu-Lin He, Dabby D. Wang, Non-NaiveBayesian Classifiers for Classification Problems with Continuous Attributes;IEEE Transactions on Cybernetics, 2013, DOI: 10.1109/TCYB.2013.2245891.(SCI)
[13] Xi-zhao Wang, Ling-Cai Dong,Jian-Hui Yan, Maximum ambiguity based sample selection in fuzzy decision treeinduction, IEEE Transactions on Knowledge and Data Engineering, 2012, 24(8):1491-1505.(SCI)
[12] Xi-zhao Wang, Chun-Ru Dong,Improving generalization of fuzzy if-then rules by maximizing fuzzy entropy,IEEE Transactions on Fuzzy Systems, 2009, 17(3): 556-567.(SCI)
[11] Xi-zhao Wang, DS Yeung, ECC Tsang,A comparative study on heuristic algorithms for generating fuzzy decisiontrees, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,2001, 31(2): 215-226.(SCI)
[10] DS Yeung, Xi-zhao Wang, ECC Tsang,Handling interaction in fuzzy production rule reasoning, IEEE Transactions onSystems, Man, and Cybernetics, Part B-Cybernetics, 2004, 34(5): 1979-1987.(SCI)
[9] DS Yeung, Xi-zhao Wang, Improvingperformance of similarity-based clustering by feature weight learning, IEEETransactions on Pattern Analysis and Machine Intelligence, 2002, 24(4):556-561.(SCI)
[8] ECC Tsang, Xi-zhao Wang, DS Yeung,Improving learning accuracy of fuzzy decision trees by hybrid neural networks,IEEE Transactions on Fuzzy Systems, 2000, 8(5): 601-614.(SCI)
[7] Daniel Yeung, Shu-Yuan Jin, Xi-zhaoWang, Covariance-matrix modeling and detecting various flooding attacks, IEEETransactions on Systems, Man, and Cybernetics, Part A: Systems and Humans,2007, 37(2): 157-169.(SCI)
[6] ECC Tsang, DS Yeung, Xi-zhao Wang,OFFSS: Optimal fuzzy-valued feature subset selection; IEEE Transactions onFuzzy Systems, 2003, 11(2): 202-213.(SCI)
[5] James N. K. Liu, Yu-Lin He, EdwardHY Lim, Xi-zhao Wang, A new method for knowledge and information managementdomain ontology graph model, IEEE Transactions on Systems, Man, andCybernetics: Systems, 2013, 43(1): 115-127.(SCI)
[4] Su-Yun Zhao, Eric C. C. Tsang,De-Gang Chen, Xi-zhao Wang, Building a rule-based classifier-a fuzzy-rough setapproach, IEEE Transactions on Knowledge and Data Engineering, 2010, 22(5):624-638.(SCI)
[3] DS Yeung, Ng Wing, De-feng Wang,Eric Tsang, Xi-zhao Wang, Localized Generalization Error Model and ItsApplication to Architecture Selection for Radial Basic Function Neural Network,IEEE Transactions on Neural Networks, 2007, 18(5): 1294-1305.(SCI)
[2] DS Yeung, De-Gang Chen, ECC Tsang,JWT Lee, Xi-zhao Wang, On the generalization of fuzzy rough sets, IEEETransactions on Fuzzy Systems, 2005, 13(3): 343-361.(SCI)
[1] ECC Tsang, DS Yeung, JWT Lee, DMHuang, Xi-zhao Wang, Refinement of generated fuzzy production rules by using afuzzy neural network, IEEE Transactions on Systems, Man, and Cybernetics, PartB: Cybernetics, 2004, 34(1): 409-418.(SCI)
Elsevier出版社
[28] Shuxia Lu, Guiqiang Zhang, Xu Zhou, Xi-zhao Wang, Computationmethods of Moore-Penrose generalized inverse matrices for extreme learningmachine, Accepted in Neurocomputing
[27] Lisha Hu, Shuxia Lu, Xi-zhao Wang,A New and Informative Active Learning Approach for Support Vector Machine,Accepted in Information Sciences
[26] Suyun Zhao, Xi-zhao Wang, DegangChen and Eric Tsang, Nested structure in parameterized rough reduction,Accepted in Information Sciences
[25] Xi-zhao Wang, Qing-Yan Shao, MiaoQing, Jun-Hai Zhai, Architecture selection for networks trained with extremelearning machine using localized generalization error model, Neurocomputing,2013, 102: 3-9.(SCI)
[24] Xi-zhao Wang, Yu-Lin He, Ling-CaiDong, et al, Particle swarm optimization for determining fuzzy measures fromdata, Information Sciences, 2011, 181(19): 4230-4252.(SCI)
[23] Xi-zhao Wang, Ai-Xia Chen, Hui-MinFeng, Upper integral network with extreme learning mechanism, Neurocomputing,2011, 74(16): 2520-2525.(SCI)
[22] Xi-zhao Wang, Jun-Hai Zhai, Shu-XiaLu, Induction of multiple fuzzy decision trees based on rough set technique,Information Sciences, 2008,178(16):3188-3202.(SCI)
[21] Xi-zhao Wang, Chun-Guo Li, ADefinition of Partial Derivative of Random Functions and Its Application toRBFNN Sensitivity Analysis, Neurocomputing, 2008, 71(7-9):1515-1526.(SCI)
[20] Xi-zhao Wang, Eric Tsang, Su-YunZhao, De-Gang Chen, Daniel Yeung, Learning fuzzy rules from fuzzy examplesbased on rough set techniques, Information Sciences, 2007, 177(20):4493-4514(SCI)
[19] Xi-zhao Wang, Chun-Ru Dong,Tie-Gang Fan, Training T-S norm neural networks to refine weights for fuzzyif-then rules, Neurocomputing, 2007, 70(13-15):2581-2587(SCI)
[18] Xi-zhao Wang, Qiang He, De-GangChen, Daniel Yeung, A genetic algorithm for solving the inverse problem ofsupport vector machines, Neurocomputing, 2005, 68:225-238.(SCI)
[17] Xi-zhao Wang, Ya-Dong Wang, Li-JuanWang, Improving fuzzy c-means clustering based on feature-weight learning,Pattern Recognition Letters, 2004, 25(10):1123-1132.(SCI)
[16] Xi-zhao Wang, Zi-Mian Zhong,Ming-Hu Ha, Iteration algorithms for solving a system of fuzzy linearequations, Fuzzy Sets and Systems, 2001, 119(1):121-128.(SCI)
[15] Xi-zhao Wang, Ya-Dong Wang, X F Xu,et al, A new approach to fuzzy rule generation: fuzzy extension matrix, FuzzySets and Systems, 2001, 123(3): 291-306.(SCI)
[14] Xi-zhao Wang, Bin Chen, Guo-Liang Qian,et al. On the optimization of fuzzy decision trees,Fuzzy Sets and Systems, 2000,112(1):117-125.(SCI)
[13] Xi-zhao Wang, Jia-Rong Hong,Learning optimization in simplifying fuzzy rules, Fuzzy Sets and Systems,1999,106(3):349-356.(SCI)
[12] Xi-zhao Wang, Jia-Rong Hong, On thehandling of fuzziness for continuous-valued attributes in decision treegeneration; Fuzzy Sets and Systems, 1998,99(3):283-290.(SCI)
[11] Xi-zhao Wang, Ming-Hu Ha, Note onmaxmin mu/E estimation, Fuzzy Sets and Systems, 1998, 94(1):71-75.(SCI)
[10] Ming-Hu Ha, Xi-zhao Wang, Lan-ZhenYang, et al; Sequences of (S) fuzzy integrable functions, Fuzzy Sets andSystems, 2003, 138 (3): 507-522.(SCI)
[9] Ming-Hu Ha, Xi-zhao Wang, Cong-XinWu, Fundamental convergence of sequences of measurable functions on fuzzymeasure space, Fuzzy Sets and Systems, 1998, 95(1): 77-81.(SCI)
[8] Ming-Hu Ha, Xi-zhao Wang, Some noteson the regularity of fuzzy measures on metric spaces, Fuzzy Sets and Systems,1997, 87(3): 385-387.(SCI)
[7] Qiang Hua, Li-jie Bai, and Xi-ZhaoWang; Local similarity and diversity preserving discriminant projection forface and handwriting digits recognition; NeuroComputing, 86:150-157, Jun. 2012.(SCI)
[6] Yu-Lin He, James N. K. Liu, Xi-zhaoWang, et al, Optimal bandwidth selection for re-substitution entropyestimation, Applied Mathematics and Computation, 2012, 219(8): 3425-3460.(SCI)
[5] De-gang Chen, Qiang He, Xi-zhaoWang, On Linear Separability of Data Sets in Feature Space, Neurocomputing,2007, 70(13):2441-2448.(SCI)
[4] Shu-yuan Jin, DS Yeung, Xi-zhaoWang, Network Intrusion Detection in Covariance Feature Space, PatternRecognition, 2007, 40(8):2185-2197.(SCI)
[3] Ming-Hu Ha, Li-Xin Cheng, Xi-zhaoWang, Notes on Riesz's theorem on fuzzy measure space, Fuzzy Sets and Systems,1997, 90(3): 361-363.(SCI)
[2] Ng Wing, DS. Yeung, M Firth, ECCTsang, Xi-zhao Wang, Feature Selection Using Localized Generalization Error forSupervised Classification Problems Using RBFNN, Pattern Recognition,2008,41(12):3706-3719.(SCI)
[1] De-Gang Chen, ECC Tsang, DS Yeung,Xi-zhao Wang, The parameterization reduction of soft sets and its applications,Computers & Mathematics with Applications, 2005,49(5-6): 757-763.(SCI)
Springer出版社
[18] Xi-zhao Wang,Su-Fang Zhang, Jun-Hai Zhai, A nonlinear integraldefined on partition and its application to decision trees, Soft Computing,2007, 11(4):317-321(SCI)
[17] Xi-zhao Wang, Chun-Guo Li, A newdefinition of sensitivity for RBFNN and its applications to feature reduction,Lecture Notes in Computer Science, 2005, 3496:81-86.(SCI)
[16] Xi-zhao Wang, Qiang He, Enhancinggeneralization capability of SVM classifiers with feature weight adjustment;Lecture Notes in Computer Science, 2004, 3213:1037-1043.(SCI)
[15] Xi-zhao Wang, Ming-Hua Zhao,Dian-Hui Wang, Selection of parameters in building fuzzy decision trees,Lecture Notes in Artificial Intelligence, 2003, 2903: 282-292.(SCI)
[14] Xi-zhao Wang, Jun Shen, Usingspecial structured fuzzy measure to represent interaction among IF-THEN rules,Lecture Notes in Artificial Intelligence, 2006, 3930: 459-466.(SCI)
[13] Xi-zhao Wang, Qiang He, Enhancinggeneralization capability of SVM classifiers with feature weight adjustment,Lecture Notes in Computer Science, 2004, 3213: 1037-1043.(SCI)
[12] Yan Li, Xi-zhao Wang, Ming-Hu Ha,An on-line Multi-CBR agent dispatching algorithm, Soft Computing, 2007,11(1):1-5.(SCI)
[11] Qiang He, Xi-zhao Wang, Jun-FenChen, et al, A parallel genetic algorithm for solving the inverse problem ofsupport vector machines, Lecture Notes in Artificial Intelligence, 2006, 3930:871-879.(SCI)
[10] John W. T. Lee, Xi-zhao Wang,Jin-Feng Wang, Reduction of attributes in ordinal decision systems, LectureNotes in Artificial Intelligence, 2006, 3930: 578-587.(SCI)
[9] Shu-Yuan Jin, DS Yeung, Xi-zhaoWang, et al, A covariance matrix based approach to Internet anomaly detection;Lecture Notes in Artificial Intelligence, 2006, 3930: 691-700; 2006
[8] De-Gang Chen, Qiang He, Xi-zhaoWang, The infinite polynomial kernel for support vector machine, Lecture Notesin Artificial Intelligence, 2005, 3584: 267-275.(SCI)
[7] Cai-Hong Sun, S. C. K. Shiu, Xi-zhaoWang, Organizing large case library by linear programming, Lecture Notes inArtificial Intelligence, 2005, 3789: 554-564.(SCI)
[6] S. C. K. Shiu, Cai-Hung Sun, Xi-zhaoWang, et al, Maintaining Case-Based Reasoning systems using fuzzy decisiontrees, Lecture Notes in Artificial Intelligence, 2001, 1898: 285-296.(SCI)
[5] Guo-Qing Cao, Simon Shiu, Xi-zhaoWang, A fuzzy-rough approach for case base maintenance, Lecture Notes inArtificial Intelligence, 2001, 2080: 118-130.(SCI)
[4] James N. K. Liu, Yu-Lin He, EdwardH. Y. Lim, Xi-zhao Wang, Domain ontology graph model and its application inChinese text classification, Neural Computing and Applications, 2012(SCI)
[3] De-Gang Chen, Qiang He, Chun-RuDong, Xi-zhao Wang, A method to construct the mapping to the feature space forthe dot product kernels, Lecture Notes in Artificial Intelligence, 2006, 3930:918-929.(SCI)
[2] DS Yeung, De-Feng Wang, Ng Wing,Eric Tsang, Xi-zhao Wang, Structured large margin machines: sensitive to datadistribution, Machine Learning, 2007,68(2):171-200.(SCI)
[1] Ng Wing, DS Yeung, De-Feng Wang,Eric Tsang, Xi-zhao Wang, Localized generalization error of Gaussian-basedclassifiers and visualization of decision boundaries; Soft Computing, 2007,11(4): 375-381.(SCI)
其他国际期刊
[7] Xi-zhao Wang, Jun-Hai Zhai, Su-Fang Zhang, A model offinite-step random walk with absorbent boundaries, International Journal ofComputer Mathematics, 2008, 85(11):1685-1696.(SCI)
[6] Xi-zhao Wang, Shu-Xia Lu, Jun-HaiZhai, Fast fuzzy multi-category SVM based on support vector domain description,International Journal of Pattern Recognition and Artificial Intelligences,2008, 22(1):109-120 (SCI)
[5] Xi-zhao Wang, Feng Guo, Xiang-HuiGao, Task 2 winner's solution: A Minkowski distance and nearest-unlike-neighbordistance method, within the paper "Qiang Yang, et al, Estimating location using Wi-Fi", IEEE Intelligent Systems, 2008, 23(1):8-13(SCI)
[4] Xi-zhao Wang, Shu-Xia Lu, Fuzzy multi-classsupport vector machine based on improved support vector data description,International Journal of Dynamics of Discrete, Continuous, and Impulse Systems,2007,14:187-192.(SCI)
[3] ECC Tsang, Xi-zhao Wang, An approachto case-based maintenance: Selecting representative cases, InternationalJournal of Pattern Recognition and Artificial Intelligence, 2005,19(1):79-89.(SCI)
[2] Shu-Yuan Jin, DS Yeung, Xi-zhaoWang, Internet anomaly detection based on statistical covariance matrix,International Journal of Pattern Recognition and Artificial Intelligences,2007,21(3):591-606.(SCI)
[1] Simon C. K. Shiu, Daniel S. Yeung,Cai-Hung Sun, Xi-zhao Wang, Transferring case knowledge to adaptationknowledge: An approach for case-base maintenance, Computational Intelligence,2001, 17(2): 295-314.(SCI)
会议论文
[67] Xi-zhao Wang, Meng Zhang, Shu-XiaLu, Xu Zhou, A total error rate multi-class classification, In Proceedings of2012 International Conference on Systems, Man, and Cybernetics, 2012, pp:964-969.(EI)
[66] Xi-zhao Wang, Qing Miao, Meng-YaoZhai, Jun-Hai Zhai, Instance selection based on sample entropy for efficientdata classification with ELM, In Proceedings of 2012 International Conferenceon Systems, Man, and Cybernetics, 2012, pp: 970-974.(EI)
[65] Hong-Jie Xing, Xi-zhao Wang,Ming-Hu Ha, A comparative experimental study of feature-weight learningapproaches, In Proceedings of 2011 International Conference on Systems, Man,and Cybernetics, 2011, pp: 3500-3505.(EI)
[64] Jun-Hai Zhai, Yuan-Yuan Gao,Meng-Yao Zhai, Xi-Zhao Wang, Rough set model and its eight extensions, InProceedings of 2011 International Conference on Systems, Man, and Cybernetics,2011, pp: 3512-3517.(EI)
[63] James N. K. Liu, Yu-Lin He, Xi-ZhaoWang, Yan-Xing Hu, A comparative study among different kernel functions inflexible naïve Bayesian classification, In Proceedings of 2011 InternationalConference on Machine Learning and Cybernetics, 2011: 638-643.(EI)
[62] Xi-Zhao Wang, Xiang-Hui Gao, QiangHe, Side effect of cut in decision tree generation for continuous attributes,In Proceedings of 2010 International Conference on Systems, Man, andCybernetics, 2010, pp: 1364-1369.(EI)
[61] Shan Su, Xi-Zhao Wang, Jun-HaiZhai, An Improved Cluster Oriented Fuzzy Decision Trees, In Proceedings of 2009International Conference on Rough Sets, Fuzzy Sets , Data Mining & GranularComputing, 2009, pp: 447-454.(EI)
[60] Ling-Cai Dong, Dan Wang, Xi-ZhaoWang, An Improved Sample Selection Algorithm in Fuzzy Decision Tree Induction,In Proceedings of 2009 International Conference on Systems, Man, andCybernetics, 2009, pp: 629-634.(EI)
[59] Ming-Zhu Lu, Philip Chen, Jian-BingHuo, Xi-Zhao Wang, Multi-Stage Decision Tree based on Inter-class and Inner-class Margin of SVM, In Proceedings of 2009 International Conference onSystems, Man, and Cybernetics, 2009, pp: 1875-1880.(EI)
[58] Ning Zhang, Xi-Zhao Wang, Tao Xiao,An Instance Selection Algorithm Based on Contribution, Proceedings of theSeventh International Conference on Machine Learning and Cybernetics,2008, pp:919-923.(EI)
[57] Feng Guo, Xi-Zhao Wang, Yan Li, ANew Algorithm for Solving Convex Hull Problem and Its Application to FeatureSelection, Proceedings of the Seventh International Conference on MachineLearning and Cybernetics, Kunming, 2008, pp: 369-373.(EI)
[56] Xi-Zhao Wang, Bo Wu, Yu-Lin He,Xiang-Hao Pei, NRMCS: Noise Removing Based on the MCS, Proceedings of theSeventh International Conference on Machine Learning and Cybernetics, 2008, pp:89-93.(EI)
[55] Xi-Zhao Wang, Jun-Hai Zhai, Su-FangZhang, Fuzzy Decision Tree Based on the Important Degree of Fuzzy Attribute,Proceedings of the Seventh International Conference on Machine Learning andCybernetics, 2008, pp: 511-516.(EI)
[54] Ming-Zhu Lu, C. L. Philip Chen,Jian-Bing Huo, Xi-Zhao Wang, Optimization of combined kernel function for SVMbased on large margin learning theory, In Proceedings of 2008 InternationalConference on Systems, Man, and Cybernetics, 2008, pp: 353-358.(EI)
[53] Hong-Jie Xing, Xi-Zhao Wang,Rui-Xian Zhu, Dan Wang, Application of kernel learning vector quantization tonovelty detection, In Proceedings of 2008 International Conference on Systems,Man, and Cybernetics, 2008, pp: 439-443.(EI)
[52] De-gang Chen, Xi-Zhao Wang, Su-YunZhao, Attribute reduction based on fuzzy rough sets, Proceedings of theInternational Conference on Rough Sets and Intelligent Systems Paradigms, 2007,381-390.
[51] Wei-Li Zhang, Xi-Zhao Wang, Featureextraction and classification for human brain CT images, Proceedings of theSixth International Conference on Machine Learning and Cybernetics, 2007, pp:1155-1159.
[50] Xi-Zhao Wang and Wei-Xi Lin,Application of inductive learning in human brain CT image recognition,Proceedings of the Sixth International Conference on Machine Learning andCybernetics, 2007, pp: 1667-1671.(EI)
[49] Xi-Zhao Wang, Xiao-Yan Liu, Yan Liand Chun-Guo Li, Norm-based localized generalization error model and itsderivation for radial basis function neural networks, Proceedings of the SixthInternational Conference on Machine Learning and Cybernetics, 2007, pp:3623-3527.(EI)
[48] Xi-Zhao Wang, Bin Wu, Jie Li, Animprovement for localized generalization error model, Proceedings of the SixthInternational Conference on Machine Learning and Cybernetics, 2007, pp:2901-2910.(EI)
[47] Xi-Zhao Wang, Jian-Hui Yan, RanWang and Chun-Ru Dong, A sample selection algorithm in fuzzy decision treeinduction and its theoretical analyses, Proceedings of 2007 IEEE InternationalConference on Systems, Man and Cybernetics, Montreal, Canada, 7-10 October2007, 3621-3626.(EI)
[46] Xi-Zhao Wang, Shu-Xia Lu andRui-Xian Zhu, Solving SVM inverse problems based on clustering, Proceedings of2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal,Canada, 7-10 October 2007, 3615-3620.(EI)
[45] Li-Mei Feng, Xi-Zhao Wang,Improving on symbolic learning system based on genetic algorithm, Proceedingsof the 2007 International Conference on Intelligent Systems and KnowledgeEngineering, Chengdu, 15-16 October 2007, 1132-1138.(EI)
[44] Jin-Yan Sun, Xi-Zhao Wang, A newmethod for constructing radial basis function neural networks, Proceedings ofthe 2007 International Conference on Intelligent Systems and KnowledgeEngineering, Chengdu, 15-16 October 2007, 1240-1245.(EI)
[43] Chen-Xiao Yang, Xi-Zhao Wang andRui-Xian Zhu, A strategy of merging branches based on margin enlargement of SVMin decision tree induction, Proceedings of 2006 IEEE International Conferenceon Systems, Man and Cybernetics, Taipei, 8-11 October 2006, 824-828.(EI)
[42] Jian-Bing Huo, Xi-Zhao Wang,Ming-Zhu Lu and Jun-Fen Chen, Induction of multi-stage decision tree,Proceedings of 2006 IEEE International Conference on Systems, Man andCybernetics, Taipei, 8-11 October 2006, 835-839.(EI)
[41] Xi-Zhao Wang and Xiang-Hui Gao, Aresearch on the relation between training ambiguity and generalizationcapability, Proceedings of the Fifth International Conference on MachineLearning and Cybernetics, Dalian, 13-16 August 2006, vol.3, 2008-2013.(EI)
[40] Miao Wang, Xi-Zhao Wang, A researchon weight acquisition of weighted fuzzy production rules based on geneticalgorithm, Proceedings of the Fifth International Conference on MachineLearning and Cybernetics, Dalian, 13-16 August 2006, 2208-2211.(EI)
[39] Xi-Zhao Wang, Shu-Xia Lu, Improved fuzzymulticategory support vector machines classifier, Proceedings of the FifthInternational Conference on Machine Learning and Cybernetics, Dalian, 13-16August 2006, 3585-3589.(EI)
[38] Xi-Zhao Wang, Ming-Zhu Lu andJian-bing Huo, Fault diagnosis of power transformer based on large marginlearning classifier, Proceedings of the Fifth International Conference onMachine Learning and Cybernetics, Dalian, 13-16 August 2006, 2886-2891.(EI)
[37] Xi-Zhao Wang, Feng Yang, Yan Li, Adiscussion on the overlapping in fuzzy production rule reasoning, Proceedingsof the Fifth International Conference on Machine Learning and Cybernetics,Dalian, 13-16 August 2006, 4557-4562.(EI)
[36] Xi-Zhao Wang, Xu-Guang Wang and JunShen, The representation of interaction among fuzzy rules, Proceedings of theFourth International Conference on Machine Learning and Cybernetics, Guangzhou,18-21 August 2005, Vol.5, 3098-3103.(EI)
[35] Xi-Zhao Wang, Jun Shen and Xu-GuangWang, Using 2-additive fuzzy measure to represent the interaction among if-thenrules, Proceedings of the Fourth International Conference on Machine Learning andCybernetics, Guangzhou, 18-21 August 2005, Vol.5, 2797-2801.(EI)
[34] Xi-Zhao Wang, Yan Ha and De-GangChen, On the reduction of fuzzy rough sets, Proceedings of the FourthInternational Conference on Machine Learning and Cybernetics, Guangzhou, 18-21August 2005, Vol.5, 3174-3178.(EI)
[33] Xi-Zhao Wang, Su-Fang Zhang andJun-Hai Zhai, A nonlinear integral defined on partition of set and itsfundamental properties, Proceedings of the Fourth International Conference onMachine Learning and Cybernetics, Guangzhou, 18-21 August 2005, Vol.5,3092-3097.(EI)
[32] Xi-Zhao Wang and Hui Zhang, Anupper bound of input perturbation for RBFNNs sensitivity analysis, Proceedingsof the Fourth International Conference on Machine Learning and Cybernetics,Guangzhou, 18-21 August 2005, Vol.8, 4704-4708.(EI)
[31] Xi-Zhao Wang and Ying Xu,Multilevel weighted fuzzy reasoning with interaction, Proceedings of 2005 IEEEInternational Conference on Systems,Man and Cybernetics, Waikoloa, Hawaii, 10-12 October2005, 708-715.(EI)
[30] Xi-Zhao Wang, Chun-Guo Li, A newdefinition of sensitivity for RBFNN and its applications to feature reduction,Proceedings of the Fourth International Conference on Machine Learning andCybernetics, Guangzhou, 18-21 August 2005, vol.1, 81-86.(EI)
[29] Juan Sun, Xi-Zhao Wang, An initialcomparison on noise resisting between crisp and fuzzy decision trees,Proceedings of the Fourth International Conference on Machine Learning andCybernetics, Guangzhou, 18-21 August 2005, Vol.4, 2545-2550.(EI)
[28] John W.T. Lee, Xi-Zhao Wang,Jin-Feng Wang, Finding reducts for ordinal decision tables, Proceedings of theFourth International Conference on Machine Learning and Cybernetics, Guangzhou,18-21 August 2005, Vol.5, 3143-3147.(EI)
[27] Xi-Zhao Wang, Chun-Ru Dong, DanielYeung, A study on generalization capability of weighted fuzzy production ruleswith maximum entropy, Proceedings of 2004 IEEE International conference onsystems, Man and cybernetics, Hague, 10-13 October, 2004,3181-3186.(EI)
[26] Xi-Zhao Wang, Xiao-Jun Wang, A newmethodology for determining fuzzy densities in the fusion model based on fuzzyintegral, Proceedings of the Third International Conference on Machine Learningand Cybernetics, Shanghai, 26-29, August, 2004, vol.4, 2028-2031.(EI)
[25] Xi-Zhao Wang, Xiao-Ying Lu, FengZhang, Feature selection based on fuzzy extension matrix for multi-classproblem. Proceedings of the Third International Conference on Machine Learningand Cybernetics, Shanghai, 26-29, August, 2004, vol.4, 2032-2035.(EI)
[24] Xi-Zhao Wang, Jun-Fen Chen,Multiple neural networks fusion model based on choquet fuzzy integral,Proceedings of the Third International Conference on Machine Learning andCybernetics, Shanghai, 26-29, August, 2004, vol.4, 2024-2027.(EI)
[23] Xi-Zhao Wang, Hui-Min Feng,Nonnegative set functions in multiple classifier fusion, Proceedings of theThird International Conference on Machine Learning and Cybernetics, Shanghai,26-29, August, 2004, vol.4, 2020-2023.(EI)
[22] Wing Ng, Daniel Yeung, Xi-ZhaoWang, Ian Cloete, A study of the difference between partial derivative andstochastic neural network sensitivity analysis, Proceedings of the ThirdInternational Conference on Machine Learning and Cybernetics, Shanghai, 26-29,August, 2004, vol.7, 4283-4288.(EI)
[21] Yong Li, Xi-Zhao Wang, Qiang Hua,Using bp-network to construct fuzzy decision tree, Proceedings of the SecondInternational Conference on Machine Learning and Cybernetics, Xi'an, 2-5, November 2003, vol.3, 1791-1795.(EI)
[20] Yan Li, Xi-Zhao Wang, Ming-Hu Ha,On-line multi-cbr agent dispatching, Proceedings of the Second InternationalConference on Machine Learning and Cybernetics, Xi'an, 2-5, November 2003, vol.4, 2071-2075.(EI)
[19] Su-Yun Zhao, Xi-Zhao Wang, A fuzzymodel of rough sets, Proceedings of the Second International Conference onMachine Learning and Cybernetics, Xi'an, 2-5, November 2003, vol.3, 1687-1691.(EI)
[18] Da-Zhong Liu, Xi-Zhao Wang, J. W.T. Lee, Ordinal fuzzy sets and rough sets, Proceedings of the SecondInternational Conference on Machine Learning and Cybernetics, Xi'an, 2-5, November 2003, vol.3, 1438-1441.(EI)
[17] Qiang He, Xi-Zhao Wang, Hong-JieXing, A fuzzy classification method based on support vector machine,Proceedings of the Second International Conference on Machine Learning andCybernetics, Xi'an, 2-5, November 2003,vol.2, 1237-1240.(EI)
[16] Qun-Feng Zhang, Xi-Zhao Wang,Jing-Hong Wang, A further study on simplification of decision tables,Proceedings of the Second International Conference on Machine Learning andCybernetics, Xi'an, 2-5, November 2003,vol.3, 1657-1661.(EI)
[15] Hua Li, Xi-Zhao Wang, Yong Li,Using mutual information for selecting continuous-valued, Proceedings of theSecond International Conference on Machine Learning and Cybernetics, Xi'an, 2-5, November 2003, vol. 3, 1496-1499.(EI)
[14] Shi-Xin Zhao, Xi-Zhao Wang, Coreand reduction from mutual relation view and their fuzzy generalization, 2003IEEE International Conference on Systems, Man & Cybernetics, Washington DC,October 6-9 2003, sessions TD2: 2611-2616.(EI)
[13] Yan Li , Ming-Hu Ha, Xi-Zhao Wang,Principle and Design of Fuzzy Controller Based on Fuzzy Learning from Examples,Proceedings of 2002 International Conference on Machine Learning and Cybernetics,Beijing, 4-5November 2002, vol. 3, 1441-1446.(EI)
[12] Dong-Mei Huang, Xi-Zhao Wang,Ming-Hu Ha, The Optimization Problem of the Fuzzy Bi-Branches Decision Trees,Proceedings of 2002 International Conference on Machine Learning and Cybernetics,Beijing, 4-5 November 2002, vol. 3, 1667-1668.(EI)
[11] Da-Zhong Liu, Xi-Zhao Wang, JohnW.T. Lee,Correlation BasedGenerating Rules for Fuzzy Classification,Proceedings of 2002 International Conference onMachine Learning and Cybernetics, Beijing,4-5 November 2002, Volume 4, pp. 1733-1736.(EI)
[10] Hong-Jie Xing, Xi-Zhao Wang, QiangHe, Hong-Wei Yang, The Multistage Support Vector Machine, Proceedings of 2002International Conference on Machine Learning and Cybernetics, Beijing, 4-5November 2002, Volume 4, pp. 1815-1818.(EI)
[9] Xi-Zhao Wang, Ming-Hua Zhao, DanielSo Yeung, Parametric Sensitivity in Building Fuzzy Decision Trees: anExperimental Analysis, Proceedings of 2002 International Conference on MachineLearning and Cybernetics, Beijing, 4-5 November 2002, Volume 4, pp. 1819-1823.(EI)
[8] Xi-Zhao Wang, Hong-Wei Yang,Ming-Hua Zhao, Juan Sun, A Decision Tree Based on Hierarchical Decomposition,Proceedings of 2002 International Conference on Machine Learning andCybernetics, Beijing, 4-5 November 2002, Volume 4, pp. 1824-1828.(EI)
[7] Li-Juan Wang, Xi-Zhao Wang, Ming-HuHa, Yin-Shan Gu, Mining the Weights of Similarity Measure Through Learning,Proceedings of 2002 International Conference on Machine Learning andCybernetics, Beijing, 4-5 November 2002, Volume 4, pp. 1837-1841.(EI)
[6] Daniel So Yeung, Juan Sun, Xi-Zhao Wang, An InitialComparison of Generalization-Capability between Crisp and Fuzzy Decision Trees,Proceedings of 2002 International Conference on Machine Learning and Cybernetics,Beijing, 4-5 November 2002, Volume 4, pp. 1846-1851.(EI)
[5] Shen-Shan Qiu, Eric C.C. Tsang,Daniel S. Yeung, Xi-Zhao Wang, Energy Function Criterion for DiscreteHopfield-Type Neural Network with Delay, Proceedings of 2002 InternationalConference on Machine Learning and Cybernetics, Beijing, 4-5 November 2002,Volume 4, pp. 2240-2244.(EI)
[4] Rui-Feng Xu, D. S. Yeung, Xi-ZhaoWang, Using neural network classifier in post-processing system for handwrittenChinese character recognition, IEEE International Conference on Systems, Man,and Cybernetics, 2001, Vol. 3, 2001, Page(s): 1497-1502.(EI)
[3] E. C. C. Tsang, D. S. Yeung, Xi-ZhaoWang, Learning weights of fuzzy production rules by a max-min neural network,IEEE International Conference on Systems, Man, and Cybernetics, Vol. 3, 2001, pp.1485-1490.(EI)
[2] Xi-Zhao Wang, D. S. Yeung, Usingfuzzy integral to modeling case-based reasoning with feature interaction, inProceedings of IEEE International Conference on Systems, Man, and Cybernetics,October 8-11, 2000, Nashville, Tennessee, USA,pp. 3660-3665.(EI)
[1] D. S. Yeung, Xi-Zhao Wang, Using aneuro-fuzzy technique to improve the clustering based on similarity, inProceedings of IEEE International Conference on IEEE International Conferenceon Systems, Man, and Cybernetics, October 8-11, 2000, Nashville, Tennessee, USA, pp. 3693-3698.(EI)
中文期刊论文
[35] 贺毅朝,王熙照,刘坤起,王彦祺,差分演化的收敛性分析与算法改进,软件学报,21:5(2010) 875-885
[34] 王熙照, 杨晨晓, 分支合并对决策树归纳学习的影响, 计算机学报, 2007, 30(8): 1251-1258.(EI)
[33] 王熙照, 安素芳, 基于极大模糊熵原理的模糊产生式规则权重获取研究, 计算机研究与发展, 2006, 43(4): 673-678.(EI)
[32] 王熙照, 赵素云, 王静红, 基于Rough集理论的模糊值属性信息表简化, 计算机研究与发展, 2004, 41(11): 1974-1981.(EI)
[31] 王熙照, 赵素云, 基于相似关系的模糊粗糙模型, 计算机科学, 2004, 31(10)A: 31-35.(EI)
[30] 王熙照, 王亚东, 湛燕, 袁方, 学习特征权值对K-均值聚类算法的优化, 计算机研究与发展, 2003, 40(6): 869-873.(EI)
[29] 哈明虎、王熙照、李艳、田大增,基于示例学习的模糊控制器原理,河北大学学报,vol.20, no.2, June 2000,pp. 116-121
[28] 王熙照、凌伟德,两种产生模糊决策树的启发式比较(英文),河北大学学报,vol.20, no.3, September2000, pp. 1-6
[27] 黄冬梅、哈明虎、王熙照,决策树与模糊决策树的比较,河北大学学报,vol.20, no.3, September2000, pp. 218-221
[26] 叶风,权光日,王熙照,基于归结的最大一般理论特化,计算机学报,22卷, 1999年12月, pp. 1233-1238
[25] 黄冬梅,王熙照,一种改进的区间值属性决策树学习算法,河北大学学报(自然科学版),vol.19, no.4, 1999.12, pp.325-328
[24] 王熙照、洪家荣,区间值属性决策树学习算法,软件学报, vol.9, no. 8, 1998, pp.637-640
[23] 钱国良、王熙照、陈彬,手写汉字特征抽取的模糊归纳学习处理,清华大学学报(自然科学版),1998年第38卷(S2), pp. 85-88
[22] 孙建平、张艳娥、王熙照,Fuzzy矩阵方程的解及性质,模糊系统与数学,1998年第12卷(第4期)pp. 72-78
[21] 仲自勉,汪浩,王熙照,带有专家部分知识的模糊学习算法及在储层识别中的应用,河北大学学报(自然科学版),vol.18, no.3, 1998.9, pp.215-218
[20] 王熙照,不精确概念的表示理论(二):抽象知识的简化与相依性,河北大学学报, vol. 2, 1997, pp. 1-5
[19] 王熙照,不精确概念的表示理论(一):定义与基础知识,河北大学学报, vol. 4, 1996, pp. 1-6
[18] 王熙照、哈明虎、史本广,一类新的模糊回归模型,兰州大学学报(模糊数学与系统专辑), vol. 32, 1996, pp. 472-475
[17] 刘会杰、王熙照,模糊示例学习的一个模型及相应的决策树算法,河北大学学报(增), 1996, pp. 1-4
[16] 哈明虎、王熙照、史本广,关于Fuzzy测度的伪零可加及伪一致自连续性,兰州大学学报, vol. 32, 1996, pp.136-139
[15] 王熙照、史本广,模糊回归模型中的变量筛选,模糊系统与数学, vol. 8, 1994, pp. 66-68
[14] 王熙照、哈明虎,一类Fuzzy距离及在回归分析中的应用,河北大学学报, vol. 4, 1994, pp. 8-13
[13] 王熙照、哈明虎,一类模糊线性方程组的迭代解法,模糊分析设计的理论与应用(主编:王彩华等,中国建筑工业出版社,1993) pp. 604-605
[12] 王熙照、哈明虎,多元Fuzzy线性回归,河北大学学报, vol. 3, 1993, pp. 8-14
[11] 王熙照、哈明虎,泛模糊积分,河北大学学报, vol. 3, 1992, pp. 18-24
[10] 王熙照、哈明虎,非线性模糊模型分析及参数估计,模糊系统与数学, vol. 6, 1992, pp. 38-41
[9] 王熙照、哈明虎、凌伟德,模糊数序列空间,模糊系统与数学, vol. 6, 1992, pp. 41-43
[8] 哈明虎、王熙照,Fuzzy测度的绝对连续性及扩张,模糊系统与数学, vol. 6, 1992, pp. 35-37
[7] 王熙照、哈明虎,由泛积分定义的模糊测度,模糊数学与系统成果会论文集(主编:曹炳元,湖南科学技术出版社,1991) pp. 61-63
[6] 哈明虎、王熙照,模糊线性回归分析及参数估计,模糊数学与系统成果会论文集(主编:曹炳元,湖南科学技术出版社,1991) pp. 19-21
[5] 哈明虎、王熙照,模糊集上模糊测度的绝对连续性及扩张,河北大学学报, vol. 4, 1991, pp. 17-22
[4] 王熙照、哈明虎,σ-可加模糊集上模糊测度,河北大学学报, vol. 1, 1991, pp. 17-24
[3] 王熙照、哈明虎,sigma-可加模糊集上的模糊测度及结构特征,中国模糊数学与模糊系统委员会第5届年会文集, (责任主编:徐扬、余孝华,西南交通大学出版社,成都,1990) pp. 57-59
[2] 哈明虎、王熙照,Fuzzy值变量线性回归的一种参数估计方法,河北大学学报, vol. 5, 1989, pp. 15-19
[1] 哈明虎、王熙照,模糊测度与收敛,河北大学学报, vol. 5, 1989, pp. 79-86