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  • 张超

    最终学位:博士

    导师类型:博士生导师

  • 电子邮箱:czhang@sxu.edu.cn

    联系电话:0351-7010566

  • 研究方向:数据挖掘、粒计算、智能决策

  • 个人简介
  • 学术论文
  • 科研项目

张超,博士毕业于山西大学系统工程专业、硕士毕业于香港大学电机电子工程专业。现为山西大学智能信息处理研究所副教授,博士生导师。研究方向为数据挖掘、粒计算、智能决策。主讲山西大学本科生“数据科学导论”和“软件工程”课程。

近年来,先后主持国家自然科学基金面上项目、青年项目和山西省重点研发计划、应用基础研究计划等科研项目10多项,省级教改项目2项。在国际期刊IEEE Transactions on Computational Social Systems, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Consumer Electronics, Information Sciences, Information Fusion, International Journal of Approximate Reasoning, Applied Soft Computing, ACM Transactions on Asian and Low-Resource Language Information Processing, Computers in Industry, Applied Mathematical Modelling,以及国内期刊《计算机研究与发展》、《控制与决策》等上发表学术论文60余篇,其中SCI期刊论文40余篇,教改论文2篇,主编专著2部,参编专著4部,获国家发明专利多项。以第一完成人身份获山西省第十一次社会科学研究优秀成果奖二等奖、山西省高等学校科学研究优秀成果奖一等奖、“百部(篇)工程”一等奖、太原市自然科学优秀学术论文一等奖、中国粒计算与知识发现会议优秀学生论文奖、中国高校计算机教育大会优秀论文一等奖等奖项。博士学位论文获ACM中国理事会太原分会优秀博士论文、山西大学优秀博士学位论文。入选山西省“三晋英才”支持计划、山西省高等学校青年科研人员培育计划、山西省科技创新青年人才团队核心成员。

中国人工智能学会粒计算与知识发现专委会委员,中国人工智能学会人工智能基础专委会委员。担任国际期刊International Journal of Cognitive Computing in Engineering和Frontiers in Artificial Intelligence编委,《计算机工程》青年编委,Brain-X特邀编辑,国际会议IEEE ISPCE-AS、NCAA、ICCSI、FSDM、IIAI AAI程序委员会委员,国际期刊International Journal of Fuzzy Systems、Intelligent Automation & Soft Computing、Electronics和International Journal of Cognitive Computing in Engineering客座主编,《计算机科学》年度“优秀审稿专家”,IEEE TFS, IEEE TCYB, IEEE TII, IEEE TCSS, IEEE TETCI, IEEE TCE, IEEE/CAA JAS, IEEE IoT-J, ACM TALLIP, INS, PR, IJAR, IPM, KBS, AIRE, ASOC, ESWA, EAAI, APIN, IJIS, SOCO, IJMLC, JIFS等多个SCI期刊审稿人。国家自然科学基金评审专家,山西省工信厅、山西省商务厅项目评审专家。曾受邀担任人工智能领域专业技术转移转化能力提升高级研修班、模糊系统与数据挖掘国际会议等多个国内外学术会议特邀报告人。

积极引导学生参与科研实践,培养学生科研能力与创新能力。多次指导研究生获研究生国家奖学金、山西省研究生教育创新项目。多次指导本科生参加国家级大学生创新创业训练计划等科研训练与学科竞赛,并发表CCF推荐国际学术会议和SCI期刊论文多篇。

[1] Chao Zhang, Juanjuan Ding, Jianming Zhan, Arun Kumar Sangaiah*, Deyu Li*. Fuzzy intelligence learning based on bounded rationality in IoMT systems: A case study in Parkinson’s disease. IEEE Transactions on Computational Social Systems, 2023, 10(4): 1607-1621.

[2] Chao Zhang, Jingjing Zhang, Wentao Li*, Witold Pedrycz, Deyu Li*. A regret theory-based multi-granularity three-way decision model with incomplete T-spherical fuzzy information and its application in forest fire management. Applied Soft Computing, 2023, 145: 110539.

[3] Chao Zhang, Xiaochuan Li, Arun Kumar Sangaiah*, Wentao Li, Baoli Wang*, Feng Cao, Xuekui Shangguan*. Collaborative fuzzy linguistic learning to low-resource and robust decision system based on bounded rationality. ACM Transactions on Asian and Low-Resource Language Information Processing, 2023, doi: 10.1145/3592605.

[4] Chao Zhang*, Juanjuan Ding, Jianming Zhan, Deyu Li. Incomplete three-way multi-attribute group decision making based on adjustable multigranulation Pythagorean fuzzy probabilistic rough sets. International Journal of Approximate Reasoning, 2022, 147: 40-59.

[5] Chao Zhang, Wenhui Bai, Deyu Li*, Jianming Zhan. Multiple attribute group decision making based on multigranulation probabilistic models, MULTIMOORA and TPOP in incomplete q-rung orthopair fuzzy information systems. International Journal of Approximate Reasoning, 2022, 143: 102-120.

[6] Chao Zhang, Juanjuan Ding, Deyu Li*, Jianming Zhan. A novel multi-granularity three-way decision making approach in q-rung orthopair fuzzy information systems. International Journal of Approximate Reasoning, 2021, 138: 161-187.

[7] Chao Zhang, Deyu Li*, Jiye Liang, Baoli Wang. MAGDM-oriented dual hesitant fuzzy multigranulation probabilistic models based on MULTIMOORA. International Journal of Machine Learning and Cybernetics, 2021, 12(5): 1219-1241.

[8] Chao Zhang, Deyu Li*, Jiye Liang. Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes. Information Sciences, 2020, 507: 665-683.

[9] Chao Zhang, Deyu Li*, Jiye Liang. Interval-valued hesitant fuzzy multi-granularity three-way decisions in consensus processes with applications to multi-attribute group decision making. Information Sciences, 2020, 511: 192-211.

[10] Chao Zhang, Deyu Li*, Xiangping Kang, Dong Song, Arun Kumar Sangaiah, Said Broumi. Neutrosophic fusion of rough set theory: An overview. Computers in Industry, 2020, 115: 103117.

[11] Chao Zhang, Deyu Li*, Yanhui Zhai, Yuanhao Yang. Multigranulation rough set model in hesitant fuzzy information systems and its application in person-job fit. International Journal of Machine Learning and Cybernetics, 2019, 10(4): 719-729.

[12] Chao Zhang, Deyu Li*, Jiye Liang. Hesitant fuzzy linguistic rough set over two universes model and its applications. International Journal of Machine Learning and Cybernetics, 2018, 9(4): 577-588.

[13] Chao Zhang, Deyu Li*, Yimin Mu, Dong Song. An interval-valued hesitant fuzzy multigranulation rough set over two universes model for steam turbine fault diagnosis. Applied Mathematical Modelling, 2017, 42: 693-704.

[14] Chao Zhang, Deyu Li*, Rui Ren. Pythagorean fuzzy multigranulation rough set over two universes and its applications in merger and acquisition. International Journal of Intelligent Systems, 2016, 31(9): 921-943.

[15] Chao Zhang, Yanhui Zhai, Deyu Li*, Yimin Mu. Steam turbine fault diagnosis based on single-valued neutrosophic multigranulation rough sets over two universes. Journal of Intelligent & Fuzzy Systems, 2016, 31(6): 2829-2837.

[16] Juanjuan Ding, Chao Zhang*, Deyu Li*, Arun Kumar Sangaiah*. Hyperautomation for air quality evaluations: A perspective of evidential three-way decision-making. Cognitive Computation, 2023, doi: 10.1007/s12559-022-10101-8.

[17] Wenhui Bai, Chao Zhang*, Yanhui Zhai*, Arun Kumar Sangaiah*. Incomplete intuitionistic fuzzy behavioral group decision-making based on multigranulation probabilistic rough sets and MULTIMOORA for water quality inspection. Journal of Intelligent & Fuzzy Systems, 2023, 44(3): 4537-4556.

[18] Tao Zhan, Wentao Li*, Chao Zhang. Discrete impulsive signal observer for fractional order control systems and its consumer electronic circuit application. IEEE Transactions on Consumer Electronics, 2023, doi: 10.1109/TCE.2023.3278299.

[19] Yu Wang, Jianming Zhan*, Chao Zhang. A three-way decision method based on prospect theory under probabilistic linguistic term sets. Information Sciences, 2023, 645: 119342.

[20] Chenglong Zhu, Xueling Ma*, Chao Zhang, Weiping Ding, Jianming Zhan*. Information granules-based long-term forecasting of time series via BPNN under three-way decision framework. Information Sciences, 2023, 634: 696-715.

[21] Wenjie Wang, Chao Zhang, Jianming Zhan*, Enrique Herrera-Viedma, Gang Kou. A regret-theory-based three-way decision method with a priori probability tolerance dominance relation in fuzzy incomplete information systems. Information Fusion, 2023, 89: 382-396.

[22] Haoxiang Zhou, Wentao Li*, Chao Zhang, Tao Zhan. Dynamic maintenance of updating rough approximations in interval-valued ordered decision systems. Applied Intelligence, 2023, doi: 10.1007/s10489-023-04655-9.

[23] Feng Cao, Bing Xing, Jiancheng Luo*, Deyu Li, Yuhua Qian, Chao Zhang, Hexiang Bai, Hu Zhang. An efficient object detection algorithm based on improved YOLOv5 for high-spatial-resolution remote sensing images. Remote Sensing, 2023, 15: 3755.

[24] Wentao Li*, Deyu Li, Huiyan Zhang, Chao Zhang, Peng Shi. Multigranulation-based double-quantitative rough sets for multi-source event-based decision systems. Transactions of the Institute of Measurement and Control, 2023, doi: 10.1177/01423312221142180.

[25] Erliang Yao, Deyu Li*, Yanhui Zhai, Chao Zhang. Multi-label feature selection based on relative discernibility pair matrix. IEEE Transactions on Fuzzy Systems, 2022, 30(7): 2388-2401.

[26] Xinru Han, Chao Zhang, Jianming Zhan*. A three-way decision method under probabilistic linguistic term sets and its application to Air Quality Index. Information Sciences, 2022, 617: 254-276.

[27] Yanhui Zhai, Jianjun Qi, Deyu Li*, Chao Zhang, Weihua Xu. The structure theorem of three-way concept lattice. International Journal of Approximate Reasoning, 2022, 146: 157-173.

[28] Xin Wen, Deyu Li*, Chao Zhang. A weighted ML-KNN based on discernibility of attributes to heterogeneous sample pairs. Information Processing & Management, 2022, 59: 103053.

[29] Wenjie Wang, Jianming Zhan*, Chao Zhang. Three-way decisions based multi-attribute decision making with probabilistic dominance relations. Information Sciences, 2021, 559: 75-96.

[30] Chao Zhang, Haonan Hou, Arun Kumar Sangaiah*, Deyu Li*, Feng Cao, Baoli Wang. Efficient mobile robot navigation based on federated learning and three-way decisions. International Conference on Neural Information Processing (ICONIP 2013), Changsha, 2023.

[31] Xueqing Fan, Chao Zhang*, Arun Kumar Sangaiah*, Yuting Cheng, Anna Wang, Liyin Wang. GCM-FL: A novel granular computing model in federated learning for fault diagnosis. International Conference on Neural Information Processing (ICONIP 2013), Changsha, 2023.

[32] Chao Zhang, Yanhui Zhai, Deyu Li*. Multigranulation rough sets in hesitant fuzzy linguistic information systems. 2016 International Joint Conference on Rough Sets (IJCRS 2016), Santiago, Chile, 2016.10.7-2016.10.11, 9920: 307-317.

[33] Wenhui Bai, Juanjuan Ding, Chao Zhang, Yanhui Zhai, Deyu Li, Said Broumi. Adjustable multigranulation SVN probabilistic rough sets with application to teamwork evaluations. Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education, IGI Global, 2023, Chapter 2.

[34] Juanjuan Ding, Wenhui Bai, Chao Zhang, Deyu Li, Said Broumi. A new neutrosophic multigranulation model for multi-attribute group decision making. Advances and Applications of Fuzzy Sets and Logic, IGI Global, 2022, Chapter 24.

[35] Rui Ren, Chao Zhang, Deyu Li. When neutrosophic theory meets three-way decisions. Neutrosophic Theories in Communication, Management and Information Technology, Nova Science Publishers, 2020, Chapter 9.

[36] 张超*, 李德玉.考虑关联性与优先关系的区间犹豫模糊图决策. 计算机研究与发展, 2019, 56(11): 2438-2447.

[37] 张超, 李德玉*, 翟岩慧. 双论域上的犹豫模糊语言多粒度粗糙集及其应用. 控制与决策, 2017, 32(1): 105-110.

[38] 张超, 李德玉*. 犹豫模糊图及其在多属性决策中的应用. 模式识别与人工智能, 2017, 30(11): 1012-1018.

[39] 王冰洁, 张超*, 李德玉, 马瑾男, 王渊. 基于区间二型模糊多粒度证据融合方法的钢铁行业耗能决策. 南京大学学报(自然科学), 2023, 56(4): 452-460.

[40] 李小川, 张超*, 李德玉, 上官学奎, 马瑾男, 陆文瑞. 基于 TPOP 法的犹豫模糊语言稳健型多粒度群决策. 南京大学学报(自然科学), 2023, 59(1): 22-34.

[41] 任睿, 张超*, 庞继芳. 有限理性下多粒度q-RO模糊粗糙集的最优粒度选择及其在并购对象选择中的应用. 南京大学学报(自然科学), 2023, 59(4): 600-609.

[42] 宋鹏, 张超*, 钱宇华. 风险厌恶视角下风险投资项目选择的群决策研究. 经济问题, 2022(10): 61-65+72.

[43] 白文慧, 张超*, 陈炜哲, 李德玉, 上官学奎, 马瑾男. 基于多粒度概率粗糙集与MULTIMOORA的q-RO模糊多属性群决策. 重庆邮电大学学报(自然科学版), 2021, 33(5): 769-779.

[44] 张晶晶, 张超*, 陈炜哲, 李德玉, 庞继芳, 王彦婕. 有限理性下基于多粒度概率粗糙集的三支球型模糊多属性群决策. 模糊系统与数学, 2022, 36(6): 12-25.

[45] 侯浩楠, 张超*, 申利华, 李德玉, 王志文, 张颖. 面向三支群决策的多粒度图像模糊概率粗糙集研究. 模糊系统与数学, 2022, 36(6): 161-174.

[46] 丁娟娟, 张超*, 申利华, 李德玉, 庞继芳, 王志文. 基于可调多粒度对偶犹豫模糊概率粗糙集的三支多属性群决策. 模糊系统与数学, 2021, 35(6): 14-27.

[47] 任睿, 张超*, 马瑾男. 基于可调多粒度q-RO模糊概率粗糙集的企业财务质量匹配. 模糊系统与数学, 2020, 34(6): 68-75.

[48] 张超, 李德玉*, 闫燕. 基于双论域犹豫三角模糊多粒度粗糙集的疾病诊断. 模糊系统与数学, 2016, 30(6): 141-148.

[49] 张超, 李德玉*. 勾股模糊粗糙集及其在多属性决策中的应用. 小型微型计算机系统, 2016, 37(7): 1531-1535.

[50] 宋鹏*, 张超. 大群体决策视角下风险投资项目选择路径研究. 山西大学学报(哲学社会科学版), 2023, 46(5): 143-151.

[51] 王斌, 梁宇栋*, 刘哲, 张超, 李德玉. 亮度自调节的无监督图像去雾与低光图像增强算法研究. 计算机科学, 2023, 50(1): 123-130.

[52] 曹峰, 李文涛, 骆剑承, 李德玉, 钱宇华, 白鹤翔, 张超. 融合光谱度量标记迁移和Tri-training的高光谱遥感图像半监督分类算法. 大数据, 2022.

[53] 翟岩慧*, 何煦, 李德玉, 张超. 融合决策蕴涵的知识图谱推理方法. 计算机科学与探索, 2022.

[54] 段菲*, 王慧敏, 张超. 面向数据表示的Cauchy非负矩阵分解. 计算机科学, 2021, 48(6): 96-102.

[55] 姚二亮, 李德玉*, 李艳红, 白鹤翔, 张超. 基于双空间模糊辨识关系的多标记特征选择. 模式识别与人工智能, 2019, 32(8): 709-717.

[56] 张超, 翟岩慧, 李德玉*. 新工科背景下思政教育融入数据科学导论课程教学探索. 计算机教育, 2023(4): 108-112.

[57] 张超*, 翟岩慧, 郑建兴, 段菲. 区域产业背景下基于项目驱动的计算机学科研究生培养模式探索. 西部素质教育, 2022, 8(5): 1-3+26.

[58] 张超. 犹豫模糊多粒度智能决策. 西安交通大学出版社, 2023.

[59] 张超, 李德玉. 多属性群决策的犹豫模糊多粒度建模. 多粒度计算与三支决策, 科学出版社, 2019, 49-74.

[60] 张超, 李德玉, 翟岩慧. 群决策的区间犹豫模糊多粒度建模方法. 粒计算、商空间及三支决策的回顾与发展, 科学出版社, 2017, 316-345.

[1] 国家自然科学基金面上项目:面向群决策的多粒度融合建模理论与方法研究(项目编号:62272284,主持),时间:2023-2026

[2] 国家自然科学基金青年项目:多属性群决策的多粒度三支建模理论与方法(项目编号:61806116,主持),时间:2019-2021

[3] 山西省重点研发计划(国际科技合作)项目:基于多粒度三支计算的山西转型综改商务智能技术研究(项目编号:201903D421041,主持),时间:2019-2022

[4] 山西省应用基础研究计划面上青年基金:面向多属性群决策的多粒度三支建模研究(项目编号:201801D221175,主持),时间:2018-2020

[5] 山西省高等学校青年科研人员培育计划:(国际合作项目,主持),时间:2019-2021

[6] 山西省高等学校优秀成果培育项目:Pythagorean Fuzzy Multigranulation Rough Set over Two Universes and Its Applications in Merger and Acquisition(项目编号:2019SK036,主持),时间:2019-2021

[7] 山西省高等学校教学改革创新项目:新工科背景下《数据科学导论》课程思政建设路径研究(项目编号:J20220061,主持),时间:2022-2024

[8] 山西省研究生教育教学改革课题:基于项目驱动的计算机学科研究生主动融入山西转型综改示范区建设路径研究(项目编号:2021YJJG041,主持),时间:2021-2023

[9] 山西省高等学校科技创新项目:多属性群决策的多粒度决策粗糙集模型研究(项目编号:201802014,主持),时间:2018-2020

[10] 山西大学—小店区产学研合作项目:信创环境下智能信息匹配与知识发现技术研发及应用 (项目编号:202003S08,主持),时间:2020-2022

[11] 山西省科技创新青年人才团队:多粒度信创计算(项目编号:202204051001015,子课题负责人),时间:2022-2025

[12] 国家自然科学基金面上项目:基于形式概念分析的关联数据知识表示与推理研究(项目编号:62072294,参与),时间:2021-2024

[13] 国家自然科学基金面上项目:基于决策蕴涵的知识表示和推理研究(项目编号:61972238,参与),时间:2020-2023

[14] 国家自然科学基金面上项目:基于标记概念监督的多标记粒计算理论与算法研究(项目编号:61672331,参与),时间:2017-2020

[15] 山西省应用基础研究计划面上青年基金:基于深度特征建模复杂降质因素的图像增强算法研究(项目编号:201901D211176,参与),时间:2019-2022

[16] 山西省筹资金资助回国留学人员科研项目:基于多机协同与知识迁移的数据标注关键技术研究(项目编号:2022-007,参与),时间:2022-2025

[17] 山西省高等学校教学改革创新项目:新工科背景下基于PBL模式的数字图像处理课程教学优化探索(项目编号:J2021083,参与),时间:2021-2023