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王熙照

(深圳大學教授)

鎖定
王熙照,男,1963年生,教授,博士生導師。曾任職河北大學數學與計算機學院院長,河北省機器學習與計算智能重點實驗室主任。
中文名
王熙照
外文名
Wang Xizhao
國    籍
中國
民    族
漢族
出生日期
1963年
畢業院校
哈爾濱工業大學
職    稱
深圳大學計算機與軟件學院教授 [3] 

王熙照個人簡介

王熙照,博士,教授,博士生導師,IEEE Fellow,2013年H因子為18。
1998年畢業於哈爾濱工業大學計算機系,獲工學博士學位(計算機應用專業);1998年至2001年赴香港理工大學計算學系合作研究,任研究員(Research Fellow);2000年10月至今任河北大學數學與計算機學院院長,2007年至今任河北省機器學習與計算智能重點實驗室主任。
主要研究方向為機器學習與不確定性信息處理,包括示例模糊表示的歸納學習、近似推理與專家系統、神經網絡敏感性分析、統計學習理論與支撐向量機、模糊測度與模糊積分、粗糙集、極速學習機(Extreme Learning Machine, ELM)和大數據機器學習理論與方法等。至今,共出版學術專著3部,教材2部;在IEEE Transactions on PAMI、Information Sciences等雜誌和會議發表學術論文150多篇,其中SCI、EI檢索100餘篇;Google Scholar 搜索顯示論文累計引用次數超過2000次,單篇最高引用超過200次。H因子2013年4月查詢為18。主持國家自然科學基金項目、教育部科學技術研究重點項目、國家發改委基金項目及河北省自然科學基金項目等20餘項;獲河北省自然科學一等獎1項,教育部高等學校科學技術獎自然科學二等獎1項,河北省自然科學三等獎2項,河北省科技進步三等獎1項;2007年入選河北省教育廳首批百名優秀創新人才支持計劃,2009年獲全國模範教師稱號。
王熙照教授是IEEESMCS董事局成員和IEEESMC計算智能專業委員會主席。2002-2012連續11年作為會議主席主持召開了由IEEESMC聯合主辦的第1至第11屆機器學習與控制論國際會議(ICMLC02-12.)。鑑於為IEEESMC協會作出的突出貢獻,王熙照教授獲得IEEESMC協會的多個獎項。
王熙照教授由於在模糊決策樹和聚類技術領域做出的突出貢獻於2012年當選為IEEE Fellow. [1] 

王熙照教育經歷

1979.09-1983.06 河北大學數學系學習
1983.07 河北大學數學系獲理學學士學位(數學專業)
1985.09-1987.07 上海交通大學應用數學系研究生班學習
1990.02 河北大學數學系獲理學碩士學位(基礎數學專業)
1995.09-1996.07 哈爾濱工業大學計算機科學與工程系學習博士學位課程
1998.09 哈爾濱工業大學計算機科學與工程系獲工學博士學位(計算機應用專業)

王熙照工作經歷

1983.07-1988.01 助教,河北大學數學系
1988.02-1993.06 講師,河北大學數學系
1993.07-1998.10 副教授,河北大學數學系,應用數學教研室主任
1998.11-2013.05 教授,河北大學數學與計算機學院
1998.09-2001.09 研究員(Research Fellow),香港理工大學計算科學系
2000.10-2013.05 教授/博導,河北大學數學與計算機學院院長

王熙照學術兼職

IEEE Fellow;IEEE-SMC董事局成員(2005, 2007-2009, 2012-2014);
IEEE-SMC計算智能技術委員會主席;
IEEE SMC Baoding Chapter 主席;
國際雜誌Machine Learning and Cybernetics主編;
國際雜誌IEEE Transactions on SMC Part(B) 副主編;
國際雜誌Information Science 副主編;
國際雜誌Pattern Recognition and Artificial Intelligence副主編;
第五屆、第六屆中國人工智能學會理事;
中國人工智能學會第六屆知識工程專業委員會副主任委員;
中國人工智能學會第五屆、第六屆機器學習專業委員會常務委員 ;
中國人工智能學會第二屆、第三屆粗糙集與軟計算專業委員會常務委員;
第一屆、第二屆河北省機器學習學會理事長 ;
第三屆河北省工業與應用數學學會副理事長;
河北省人工智能學會副理事長;
河北省數學建模組委會主任;
《模糊系統與數學》雜誌編委

王熙照科研項目

28. 2013.01-2015.12 (主持) 河北省自然科學基金項目:主動學習中的不確定性及其應用研究 (項目編號:F2013201110,RMB50,000)
27. 2012.01-2015.12 (主持) 國家自然科學基金項目:歸納學習中的不確定性研究 (項目編號:61170040,RMB560,000)
26. 2010.01-2012.12 (主持) 河北省教育廳重點項目:基於不確定約簡的海量數據挖掘 (項目編號:ZD2010139,RMB50,000)
25. 2008.01-2010.12 (主持) 河北省應用基礎研究重點項目:異常點挖掘研究及其應用 (項目編號:08963522D,RMB100,000)
24. 2008.01-2010.12 (主持) 河北省自然科學基金項目:基於最大Margin的決策樹歸納學習系統及在多光譜數據分類中的應用 (項目編號:F2008000635, RMB50,000)
23. 2007.01-2009.12 (主持) 河北省教育廳首批百名優秀創新人才支持計劃 (RMB200,000.)
22. 2005.09-2008.09 (主研) 國家自然科學基金項目:基於不確定信息的確統計學習理論 (項目編號:60573069, RMB200,000)
21. 2005.01-2007.12 (主持) 國家自然科學基金項目:加權模糊規則泛化的能力研究 (項目編號:60473045,RMB180,000,結題為優)
20. 2004.08-2006.12 (參加) 香港RGC基金資助項目:基於模糊粗糙集的模糊規則抽取與模糊屬性約減
19. 2004.01-2006.12 (主持) 國家發展改革委員會項目:電力智能服務系統 (項目編號:2003-1954,RMB1,200,000)
18. 2003.01-2005.12 (主持) 河北省教育廳博士基金:模糊神經網絡研究及其在規則學習中的應用 (項目編號:B2003117,RMB40,000)
17. 2003.01-2005.12 (主持) 教育部科學技術研究重點項目:帶有互動因子的模糊推理研究(項目編號:03017,RMB50,000,2007年獲教育部高等學校科學技術獎自然科學二等獎)
16. 2002.01-2004.12(主持)河北省教育廳基金項目:模糊推理中的交互影響研究(項目編號:2002159,RMB15,000,2007年獲河北省自然科學三等獎)
15. 2003.01-2005.12 (主持) 河北省自然科學基金項目:模糊值屬性特徵子集的選取(項目編號:603137,RMB100,000,2007年獲河北省自然科學一等獎)
14. 2002.01-2004.12(主研)河北省教育廳基金項目:Internet上用户訪問信息的挖掘及應用(項目編號:2001206,RMB10,000,2007年河北省科技進步三等獎)
13. 2002.01-2003.12 (主持) 河北省教育廳基金項目:中文文本挖掘及其應用研究 (項目編號:2002154,RMB10,000)
12. 2001.01-2002.12 (主持) 河北大學博士基金資助項目:基於模糊積分的神經網絡融合 (RMB25,000)
11. 1998.09-2001.09 (Research Fellow) 項目標題:模糊值特徵子集的最優選取,RGC基金資助 (項目編號:G-T209,資助基金:港幣200,000元,項目申請者:Eric Tsang博士)
10. 1998.09-2001.09 (Research Fellow) 項目標題:基於相似性的帶有交互影響的模糊推理,RGC基金資助 (項目編號:G-T210,資助基金:港幣200,000元,項目申請者:Daniel Yeung教授)
9. 1998.09-2001.09 (Research Fellow) 項目標題:結合基於案例的推理和模糊規則歸納於系統維護,RGC基金資助 (項目編號:G-V957,資助基金:港幣429,880元,項目申請者:Simon Shiu博士)
8. 1998.09-2001.09 (Research Fellow) 項目標題:學習特徵權-基於案例的推理系統的維護方法,RGC基金資助 (項目編號:A-PA88,資助基金:港幣180,000元,項目申請者:Eric Tsang博士)
7. 1998.09-2001.09 (Research Fellow) 項目標題:基於案例的模糊專家系統的校驗,計算機系研究基金資助 (項目編號:PA25,資助基金:港幣150,000元,項目申請者:Simon Shiu 博士)
6. 1998.09-2001.09 (Research Fellow) 項目標題:模糊技術在智能混合系統中的應用,香港理工大學合作研究基金資助 (項目編號:G-YY12,資助基金:港幣1,194,000元,項目申請者:香港理工大學計算科學系楊蘇教授)
5. 1998.01-2000.12 (主持) 河北省自然科學基金資助項目:基於模糊信息的示例學習理論和算法(項目編號:698139, RMB40,000,2003年獲河北省自然科學三等獎)
4. 1997.06-1998.05 (主持) 遼河油田勘探開發研究院課題:雷14-20井區儲層橫向預測 (項目編號:雷14-20, RMB120,000)
3. 1997.01-1999.12 (參加) 河北省自然科學基金資助項目:模糊控制理論及其應用 (項目編號:97543306D, RMB40,000)
2. 1991.01-1993.06 (參加) 河北省自然科學基金資助項目:不精確信息的定量表示與不確定性數據庫理論 (1994年獲省教委科技進步2等獎)
1. 1989.01-1992.01 (參加) 國家自然科學基金資助項目:模糊信息處理的數學基礎 (1993年獲河北省教委科技進步2等獎) [1] 

王熙照獲獎情況

12.IEEE-SMC最活躍SMC技術委員會獎,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傑出Chapter獎,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.河北省自然科學1等獎,第1完成人,(河北省自然科學基金項目:模糊值屬性特徵子集的選取),2007
9. 教育部高等學校科學技術獎自然科學2等獎,第4完成人,(項目名稱:複雜不確定環境下軟計算技術及其應用),2007
8. 河北省自然科學3等獎,第1完成人,(教育部科學技術研究重點項目和教育廳項目:帶有交互作用的模糊分類和模糊推理研究) ,2007
7. 河北省科技進步3等獎,第2完成人,(河北省教育廳項目:Internet上用户訪問信息與中文文本信息的挖掘及應用) ,2007
6. IEEETransactions on SMC Part B最佳副主編獎,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傑出貢獻獎,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. 河北省自然科學3等獎,第1完成人,(河北省自然科學基金項目: 基於模糊信息的示例學習理論和算法),2003
3. 黑龍江省科技進步1等獎,第8完成人,(項目名稱:農業專家系統及其開發工具研究) ,2002
2. 河北省教委科技進步2等獎,第3完成人,(河北省自然科學基金資助項目: 不精確信息的定量表示與不確定性數據庫理論),1994
1. 河北省教委科技進步2等獎,第2完成人,(國家自然科學基金資助項目: 模糊信息處理的數學基礎),1993

王熙照學術交流

38.第三屆極速學習機國際研討會,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,韓國
36.International Conference onMachine Learning and Cybernetics,2012年7月15日-17日,西安
35.第二屆極速學習機國際研討會,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.第一屆極速學習機國際研討會,2010年12月7日,澳大利亞
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,青島
30.中國數據挖掘會議,2010年5月6日-9日,廣州
29.International Conference onRough Sets, Fuzzy sets, Data mining and Granular Computer,2009年12月18-23日,印度理工大學,新德里
28.IEEE InternationalConference on Systems, Man & Cybernetics,2009年10月11日-14日,美國
27.International Conference onMachine Learning and Cybernetics,2009年7月12日-15日,保定
26.第14屆中國模糊系統與模糊數學大會,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屆中國機器學習學術會議,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,大連
19.Asia-Pacific Workshop onVisual Information Processing,2005年12月11日-13日,香港
18.中國人工智能學會第11屆全國學術年會,2005年10月31日-11月2日,武漢
17.IEEE InternationalConference on Systems, Man & Cybernetics,2005年10月10日-12日,美國
16.International Conference onMachine Learning and Cybernetics,2005年8月19日-21日,廣州
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,荷蘭
13.International Conference onMachine Learning and Cybernetics,2004 年8月26日-29日,上海
12.中國人工智能學會第10屆全國學術年會,2003年11月,廣州
11.International Conference onMachine Learning and Cybernetics,2003年11月2日-5日,西安
10.中國人工智能學會機器學習8屆學術會,2002年12月,廣州
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,美國
6. IEEE InternationalConference on Systems, Man & Cybernetics,1999年10月12日-15日,日本
5.中國模糊數學與模糊系統委員會第9屆年會,1998年8月,保定
4.中國模糊數學與模糊系統委員會第7屆年會,1994年8月,太原
3.中國模糊數學與模糊系統委員會第6屆年會,1992年8月,黃山
2. Sino-Japan Joint Meetingon Advanced Fuzzy Sets and Systems,1990年,北京
1.中國模糊數學與模糊系統委員會第5屆年會,1990年8月,成都

王熙照大會報告

26.2013年4月28日,哈爾濱工業大學深圳研究生院,深圳,報告題目:New Advances in Architecture Selection of Random Weight Networks
25.2012年12月21日,香港城市大學,香港,報告題目:Architecture Selection ofELMs and Their Improved Training Algorithms
24.2012年12月12日,2012 InternationalSymposium on Extreme Learning Machines,新加坡,報告題目:Architecture Selection of ELMs and Their ImprovedTraining Algorithms
23.2012年12月9日,馬來西亞科技大學,馬來西亞,報告題目:Architecture Selection ofRWNs and Their Improved Training Algorithms
22.2012年11月28日,Swinburne University,墨爾本,澳大利亞,報告題目:Architecture Selection ofELMs and Their Improved Training Algorithms
21.2012年11月27日,The 1st Computer Science Workshop in La TrobeUniversity,墨爾本,澳大利亞,報告題目:Architecture Selection ofELMs and Their Improved Training Algorithms
20.2012年10月14-17日,韓國首爾,參加IEEE-SMC年會、董事會並作大會主題報告
19.2012年9月29日,廣州工業大學,廣州,報告題目:Handling Uncertainty inSupervised Learning
18.2012年4月28日,華南理工大學,廣州,報告題目:Handling Uncertainty inSupervised Learning
17.2012年4月25日,河南師範大學,新鄉,報告題目:Uncertainty in ExtremeLearning Machine
16.2012年3月12日,蘇州大學973項目研討會議,蘇州,報告題目:Intelligent InformationSystem and Learning in Uncertain Environments
15.2011年11月10日,IEEE-SMC Distinguished Lecture Program,香港城市大學,香港,報告題目:Handling Uncertainty inSupervised Learning
14.2011年11月2日,河北大學,保定,報告題目:Handling Uncertainty inSupervised Learning
13.2011年9月7日,IEEE-SMC Distinguished Lecture Program,香港理工大學,香港,報告題目:Different Writing: fromAcademic Papers to Research Proposals
12.2011年8月29日,中山大學,廣州,報告題目:Handling Uncertainty inSupervised Learning
11.2011年8月26日,IEEE-SMC Distinguished Lecture Program,香港理工大學,香港,報告題目:Handling Uncertainty inSupervised Learning
10.2010年6月,新鄉大學,新鄉,報告題目:Inverse Problem of SupportVector Machines and Its Applications
9. 2009年8月,the 9th Conference of ChinaRough Set and Soft Computing,河北師範大學,石家莊,報告題目:A Comparative Study on RuleGeneration Between Decision-tree-based and Rough-set-based Approaches
8. 2009年5月10日,浙江海洋大學,舟山,報告題目:Sample Selection Based onMaximum Uncertainty
7. 2008年12月8日,IEEE-SMC Distinguished Lecture Program,台灣科技大學,台灣,報告題目:Sample Selection Based onMaximum Uncertainty
6. 2008年12月5日,2008 Workshop on Consumer Electronics,景文科技大學,台灣,報告題目:Fuzzy Integral and ItsApplication to Classification
5. 2008年10月31日,14屆中國模糊數學與模糊系統會議,福建,報告題目:Fuzzy Integral and ItsApplication to Classification
4. 2008年9月22日,IEEE-SMC Distinguished Lecture Program,香港城市大學,香港,報告題目:Fuzzy Integral and ItsApplication to Classification
3. 2006年9月18日,2006 Asian Fuzzy Systems Society InternationalConference,保定,報告題目:Information Fusion based onFuzzy Integrals and Its Application to Classification
2. 2006年10月10日,13屆中國模糊數學與模糊系統會議,陝西師範大學,西安,報告題目: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,大連,報告題目:SVM Inverse Problem and ItsApplication to Decision Tree Induction [1] 

王熙照學術服務

會議主席: ICMLC (International Conference on Machine Learning and Cybernetics) 2002-2013
ICWAPR (International Conference on Wavelet Analysis and Pattern Recognition) 2009-2013
評審主席: CYBCONF2013 (IEEE International Conference on Cybernetics)
組織主席: ELM2011 (The International Symposium on Extreme Learning Machines)
程序主席: 第十四屆全國機器學習會議,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

王熙照學術簡介

王熙照編輯專刊

[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) [2] 
[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] “模糊集理論與應用”, 中國模糊數學與模糊系統委員會第九屆年會論文選集,劉應明、吳從忻、王熙照,1998年

王熙照專著教材

[5] 王熙照,翟俊海,基於不確定性的決策樹歸納,科學出版社,2012年
[4] 王熙照,模糊測度和模糊積分及在分類技術中的應用,科學出版社,2008年
[3] 王熙照,哈明虎,模糊示例學習與模糊控制,河北大學出版社,2002年
[2] 王熙照,概率論與數理統計,科學出版社, 2009年
[1] 王熙照,陳昊,湛燕,“數據庫原理及其應用”,河北人民出版社,2005年

王熙照期刊論文

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)
其他國際期刊
[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)
會議論文
[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 [1]  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)
中文期刊論文
[35] 賀毅朝,王熙照,劉坤起,王彥祺,差分演化的收斂性分析與算法改進,軟件學報,21:5(2010) 875-885
[34] 王熙照, 楊晨曉, 分支合併對決策樹歸納學習的影響, 計算機學報, 2007, 30(8): 1251-1258.(EI)
[33] 王熙照, 安素芳, 基於極大模糊熵原理的模糊產生式規則權重獲取研究, 計算機研究與發展, 2006, 43(4): 673-678.(EI)
[32] 王熙照, 趙素雲, 王靜紅, 基於Rough集理論的模糊值屬性信息表簡化, 計算機研究與發展, 2004, 41(11): 1974-1981.(EI)
[31] 王熙照, 趙素雲, 基於相似關係的模糊粗糙模型, 計算機科學, 2004, 31(10)A: 31-35.(EI)
[30] 王熙照, 王亞東, 湛燕, 袁方, 學習特徵權值對K-均值聚類算法的優化, 計算機研究與發展, 2003, 40(6): 869-873.(EI)
[29] 哈明虎、王熙照、李豔、田大增,基於示例學習的模糊控制器原理,河北大學學報,vol.20, no.2, June 2000,pp. 116-121
[28] 王熙照、凌偉德,兩種產生模糊決策樹的啓發式比較(英文),河北大學學報,vol.20, no.3, September2000, pp. 1-6
[27] 黃冬梅、哈明虎、王熙照,決策樹與模糊決策樹的比較,河北大學學報,vol.20, no.3, September2000, pp. 218-221
[26] 葉風,權光日,王熙照,基於歸結的最大一般理論特化,計算機學報,22卷, 1999年12月, pp. 1233-1238
[25] 黃冬梅,王熙照,一種改進的區間值屬性決策樹學習算法,河北大學學報(自然科學版),vol.19, no.4, 1999.12, pp.325-328
[24] 王熙照、洪家榮,區間值屬性決策樹學習算法,軟件學報, vol.9, no. 8, 1998, pp.637-640
[23] 錢國良、王熙照、陳彬,手寫漢字特徵抽取的模糊歸納學習處理,清華大學學報(自然科學版),1998年第38卷(S2., pp. 85-88)
[22] 孫建平、張豔娥、王熙照,Fuzzy矩陣方程的解及性質,模糊系統與數學,1998年第12卷(第4期)pp. 72-78
[21] 仲自勉,汪浩,王熙照,帶有專家部分知識的模糊學習算法及在儲層識別中的應用,河北大學學報(自然科學版),vol.18, no.3, 1998.9, pp.215-218
[20] 王熙照,不精確概念的表示理論(二):抽象知識的簡化與相依性,河北大學學報, vol. 2, 1997, pp. 1-5
[19] 王熙照,不精確概念的表示理論(一):定義與基礎知識,河北大學學報, vol. 4, 1996, pp. 1-6
[18] 王熙照、哈明虎、史本廣,一類新的模糊迴歸模型,蘭州大學學報(模糊數學與系統專輯), vol. 32, 1996, pp. 472-475
[17] 劉會傑、王熙照,模糊示例學習的一個模型及相應的決策樹算法,河北大學學報(增), 1996, pp. 1-4
[16] 哈明虎、王熙照、史本廣,關於Fuzzy測度的偽零可加及偽一致自連續性,蘭州大學學報, vol. 32, 1996, pp.136-139
[15] 王熙照、史本廣,模糊迴歸模型中的變量篩選,模糊系統與數學, vol. 8, 1994, pp. 66-68
[14] 王熙照、哈明虎,一類Fuzzy距離及在迴歸分析中的應用,河北大學學報, vol. 4, 1994, pp. 8-13
[13] 王熙照、哈明虎,一類模糊線性方程組的迭代解法,模糊分析設計的理論與應用(主編:王彩華等,中國建築工業出版社,1993) pp. 604-605
[12] 王熙照、哈明虎,多元Fuzzy線性迴歸,河北大學學報, vol. 3, 1993, pp. 8-14
[11] 王熙照、哈明虎,泛模糊積分,河北大學學報, vol. 3, 1992, pp. 18-24
[10] 王熙照、哈明虎,非線性模糊模型分析及參數估計,模糊系統與數學, vol. 6, 1992, pp. 38-41
[9] 王熙照、哈明虎、凌偉德,模糊數序列空間,模糊系統與數學, vol. 6, 1992, pp. 41-43
[8] 哈明虎、王熙照,Fuzzy測度的絕對連續性及擴張,模糊系統與數學, vol. 6, 1992, pp. 35-37
[7] 王熙照、哈明虎,由泛積分定義的模糊測度,模糊數學與系統成果會論文集(主編:曹炳元,湖南科學技術出版社,1991) pp. 61-63
[6] 哈明虎、王熙照,模糊線性迴歸分析及參數估計,模糊數學與系統成果會論文集(主編:曹炳元,湖南科學技術出版社,1991) pp. 19-21
[5] 哈明虎、王熙照,模糊集上模糊測度的絕對連續性及擴張,河北大學學報, vol. 4, 1991, pp. 17-22
[4] 王熙照、哈明虎,σ-可加模糊集上模糊測度,河北大學學報, vol. 1, 1991, pp. 17-24
[3] 王熙照、哈明虎,sigma-可加模糊集上的模糊測度及結構特徵,中國模糊數學與模糊系統委員會第5屆年會文集, (責任主編:徐揚、餘孝華,西南交通大學出版社,成都,1990) pp. 57-59
[2] 哈明虎、王熙照,Fuzzy值變量線性迴歸的一種參數估計方法,河北大學學報, vol. 5, 1989, pp. 15-19
[1] 哈明虎、王熙照,模糊測度與收斂,河北大學學報, vol. 5, 1989, pp. 79-86 [1] 
參考資料