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个人简介

罗敏霞,女,博士,教授,硕士研究生导师。西北工业大学计算机学院获工学博士; 陕西师范大学数学与信息科学学院获理学硕士学位;山西师范大学数学系获理学学士。担任中国人工智能学会人工智能基础专业委员会常务委员;中国逻辑学会非经典逻辑与计算专委会委员;国际信息研究学会中国分会人工智能专业委员会专家委员。主要研究方向为计算机科学中的非经典逻辑、模糊推理算法与图像处理等。先后在国际国内专业领域的期刊上发表论文120余篇,2篇ESI高被引论文,SCI/EI检索70余篇。主持国家自然科学面上项目2项,主持完成省级项目2项;参与多项国家自然科学基金项目。多篇论文获省自然科学优秀论文奖;作为主要成员参与的项目“泛逻辑学原理及其应用研究”分别获“陕西省教育厅高等学校科学技术一等奖”与“陕西省科学技术三等奖”。近年来,一直讲授本科生的《高等代数》、《近世代数》、研究生的《代数学》与《模糊逻辑》等课程。 在研课题 主持国家自然科学基金面上项目《近似推理的区间值模型及其逻辑基础》,60万,批准号:61773019,执行时间:2018.1-2021.12 获奖情况 (1)论文“Relationshipbetweenthequasi-idealadequatetransversalsofanabundantsemigroup”获“陕西省自然科学优秀学术论文三等奖”; (2)参与的项目“泛逻辑学原理及其应用研究”获“陕西省政府科学技术成果三等奖”; (3)参与的项目“泛逻辑学原理及其应用研究”获“陕西省高等学校科学技术成果一等奖”。 主持完成的科研项目 (1)主持完成国家自然科学基金项目“非可换逻辑证明论与模糊推理算法研究”(No.61273018) (2)主持完成省自然科学基金项目“基于子结构模糊逻辑的希尔伯特系统的构建与模糊推理算法研究”(No.Y1110651) (3)主持完成省级项目“泛逻辑在计算机中的应用”(No.20050525)

研究领域

模糊逻辑与近似推理多属性决策模式识别/医疗诊断人工智能基础理论

近期论文

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近年发表的论著与论文: 专著:  罗敏霞, 何华灿.《泛逻辑学语构理论》. 北京: 科学出版社. 论文: 1. Minxia Luo*, Ruirui Zhao, Bei Liu, Jingjing Liang. Interval-valued fuzzy reasoning algorithms based on Schweizer-Sklar t-norms and its application. Engineering Applications of Artificial Intelligence, 87 (2020) 103313.(SCI二区) 2. Minxia Luo*, Lixian Wu, Kaiyan zhou, Huarong Zhang. Multi-criteria Decision Making Method based on the Single Valued Neutrosophic Sets, Intelligent & Fuzzy Systems, 2019, 37(2), 2403-2417. (SCI) 3.  Minxia Luo*, Jingjing Liang.  A Novel Similarity Measure for Interval-Valued Intuitionistic Fuzzy Sets and Its Applications, Symmetry, 2018, (10)10: 1-13.(SCI) 4. Minxia Luo*, Kaiyan Zhou. Logical foundation of the quintuple implication inference methods, International Journal of Approximate Reasoning, 2018, 101:1-9. (SCI二区) 5. Minxia Luo*, Ruirui Zhao. A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis, Artificial Intelligence in Medicine, 2018, 89, 34-39. (SCI三区)  6. Minxia Luo*, Ruirui Zhao. Fuzzy reasoning algorithms based on similarity. Journal of Intelligent & Fuzzy Systems, 2018, 34(1): 213-219.(SCI) 7. Minxia Luo*, Xiaoling Zhou. Interval-valued Quintuple Implication Principle of fuzzy reasoning. International Journal of Approximate Reasoning, 2017, 84: 23-32.(SCI二区) 8. Minxia Luo*, Bei Liu. Robustness of interval-valued fuzzy inference triple I algorithms based on normalized Minkowski distance. Journal of Logical and Algebraic Methods in Programming, 2017, 86(1): 298-307. (SCI三区) 9. Minxia Luo*, Ze Cheng. Robustness of Fuzzy Reasoning Based on Schweizer-Sklar  Interval-valued t-norms, Fuzzy Information and Engineering, 2016, 8(2): 183-198.  10. 罗敏霞*,王雅萍. 基于Schweizer-Sklar三角范数簇的反向三I算法的鲁棒性,电子学报, 2016, Vol. 44 (4): 959-966. (EI) 11. Minxia Luo*, Yaping Wang. Robustness of Triple I Algorithms Based on Schweizer-Sklar Operators in Fuzzy Reasoning, International Journal of Advanced Computer Research, 2016, 6(22): 1-8. 12. Minxia Luo*, Ze Cheng, Jiao Wu. Robustness of interval-valued universal triple I algorithms, Journal of Intelligent & Fuzzy Systems, 2016, 30(3): 1619-1628.(SCI) 13. Minxia Luo*, Xiaoling Zhou. Robustness of reverse triple I algorithms based on interval-valued fuzzy inference, International Journal of Approximate Reasoning, 2015, 66:16-26. (SCI二区) 14. Minxia Luo*, Kai Zhang. Robustness of full implication algorithms based on interval-valued fuzzy inference, International Journal of Approximate Reasoning, 2015, 62: 61-72. (SCI二区) 15. Kai Zhang, Minxia Luo*. Outlier-robust extreme learning machine for regression problems, Neurocomputing,  2015, 151(3): 1519-1527. (SCI二区) 16. Minxia Luo*, Kai Zhang. A hybrid approach combining extreme learning machine and sparse representation for image classification, Engineering Applications of Artificial Intelligence, 2014, 27: 228-235. (SCI二区) 17. Kai Zhang, Minxia Luo. Similarity based Sparse Representation for Classification, Journal of Computational Information Systems, 2013, 9(24): 9865-9873. (EI) 18. Minxia Luo*, Ning Yao. Triple I Algorithms Based on Schweizer-Sklar Operators in Fuzzy Reasoning, International Journal of Approximate Reasoning,2013,54:640-652.(SCI二区) 19. Minxia Luo, Ni Sang, Kai Zhang. Differently Implicational Universal Triple I Algorithms of (1,2,1) Type. Journal of Computational Information Systems, 2013,9(4): 374-382.(EI) 20. Minxia Luo*, Ni Sang, Kai Zhang. The Formal Triple I  Inference Method for Logic  System  W*UL. Journal of Theoretical and Applied Information Technology, 2013, 48(1): 403-410. (EI) 21. Minxia Luo*, Ni Sang, Kai Zhang. Differently Implicational Universal Triple I Algorithms of (1,2,1) Type. Journal of Computational Information Systems, 2013,9(2): 765-772.(EI) 

学术兼职

担任中国人工智能学会人工智能基础专业委员会常务委员;中国逻辑学会非经典逻辑与计算专委会委员;国际信息研究学会中国分会人工智能专业委员会专家委员。

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