职  称:讲师
研究方向:数据挖掘、机器学习,人工智能
办公电话:15004314196
办公地点:信息科学与技术学院221室
电子邮件:jijc100@nenu.edu.cn

个人简历

冀进朝,讲师,工学博士。主持国家自然科学基金青年项目1项、参与国家自然科学基金面上项目两项,主持吉林省科技发展计划科技创新人才培育-青年科研基金项目1项、吉林省教育厅“十三五”科学技术研究项目1项、符号计算与知识工程教育部重点实验室开放课题1项。主要从事数据挖掘、机器学习、人工智能等领域的研究工作。 教育背景及工作经历 2010/09-2013/07,吉林大学,计算机科学与信息技术学院,博士 2013/07-2015/12,东北师范大学,数学与统计学院,统计学,博士后 2013/07-至今,东北师范大学,信息科学与技术学院,讲师 研究方向:数据挖掘,机器学习,人工智能 项目情况: 1.国家自然科学青年基金,混合属性条件下的聚类分析方法研究,61502093,23.8万,主持; 2.国家自然科学基金面上项目,网络学习空间中的学习风险预警模型和干预机制研究,62077012,48万,参加; 3.国家自然科学基金青年项目,基于在线学习的约束求解方法研究,61802056,24万,参加 4.吉林省科技厅青年项目,混合属性数据的聚类问题研究,5.0万,主持; 5.吉林省教育厅项目,面向高维混合属性数据的聚类方法研究,,3.0万,主持; 6.青年教师科研发展基金,高维多类型属性条件下的聚类机制研究, 30.0万,主持; 7.符号计算与知识工程教育部重点实验室开放课题,高维混合属性条件下的聚类模型和算法研究, 2万,主持; 论文情况: 1.Jinchao Ji, Ruonan Li, Wei Pang**, Fei He, Guozhong Feng, Xiaowei Zhao*, A multi-view clustering algorithm for mixed numeric and categorical data, IEEE ACCESS, 2021, 9, pp.24913-24924. 2.Jinchao Ji, Wei Pang**, Zairong Li, Fei He, Guozhong Feng, Xiaowei Zhao*, Clustering mixed numeric and categorical data with cuckoo search,IEEE ACCESS, 2020, 8, pp. 30988-31003. 3.Jinchao Ji, Yongbing Chen, Guozhong Feng, Xiaowei Zhao*, Fei He**, Clustering mixed numeric and categorical data with artificial bee colony strategy, Journal of Intelligent & Fuzzy Systems, 2019, 36, pp. 1521–1530. 4.Jinchao Ji, Wei Pang, Yanlin Zheng, Zhe Wang, Zhiqiang Ma*, An initialization method for clustering mixed numeric and categorical data based on the density and distance, International Journal of Pattern Recognition and Artificial Intelligence, 2015, 29(7), pp. 1550024-1~ 1550024-16. 5.Jinchao Ji, Wei Pang*, Yanlin Zheng, Zhe Wang, Zhiqiang Ma**, A novel artificial bee colony based clustering algorithm for categorical data, PLOS ONE, 2015, 10(5), pp. 0127125-1~0127125-17. 6.Xiaowei Zhao, Ye Zhang, Qiao Ning, Rongrui Zhang, Jinchao Ji*, Minghao Yin**, Identifying N6-methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer, Journal of Theoretical Biology, 2019, 467, pp. 39-47. 7.Pingping Sun, Yongbing Chen, Bo Liu, Yanxin Gao, Ye Han, Fei He*, Jinchao Ji**, DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning, Mathematical Biosciences and Engineering, 2019, 16(6), pp. 6231-6241. 8.Jinchao Ji, Wei Pang*, Yanlin Zheng, Zhe Wang, Zhiqiang Ma*, Libiao Zhang**, A novel cluster center initialization method for the k-prototypes algorithms using centrality and distance, APPLIED MATHEMATICS & INFORMATION SCIENCES,2015, 9(6), pp. 2933-2942. 9.冀进朝,赵晓威,何飞,胡英慧,白天,李在荣*,基于模糊质心的混合属性数据模糊加权聚类算法,计算机科学,2018,45(2), pp. 109-113. 10.Jinchao Ji, Tian Bai, Chunguang Zhou, Chao Ma, Zhe Wang, An improved k-prototypes clustering algorithm for mixed numeric and categorical data, Neurocomputing, 2013, 120, pp. 590–596. 11.Jinchao Ji, Wei Pang, Chunguang Zhou, Xiao Han, Zhe Wang, A fuzzy k-prototype clustering algorithm for mixed numeric and categorical data, Knowledge-based Systems, 2012, 30(1), pp. 129-135. 12. Yanwen Li, Feng Pu, Yu Feng, Jinchao Ji, Hongguang Sun, Han Wang, MRMD-Palm: A novel method for the identification of palmitoylated protein,CHEMOMETR INTELL LAB,2021年. 13. Xiao Han,Jinchao Ji,Positive, negative and mixed-type solutions for periodic vector differential equations,ROCKY MT J MATH,2014年 14. Xiaosa Zhao,Lingling Bao,Qiao Ning, Jinchao Ji, Xiaowei Zhao,An Improved Binary Differential Evolution Algorithm for Feature Selection in Molecular Signatures,Molecular Informatics,2018年 15. Fei He,Ye Han,Han Wang,Jinchao Ji,Yanning Liu,Zhiqiang Ma,Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network,J ELECTRON IMAGING(26卷2期023005-1-13页),2017年 16. Chuan Wan,Yuling Wang,Yaozhe Liu,Jinchao Ji, Guozhong Feng,Composite Feature Extraction and Selection for Text Classification,IEEE ACCESS,2019年 17.Qiao ning,Miao Yu,Jinchao Ji,Zhiqiang Ma**,Xiaowei Zhao*,Analysis and prediction of human acetylation using a cascade classifier based on support vector machine,BMC BIOINFORMATICS,20,346-1-15, 2019年.

社会兼职

获奖情况 (数据来源:科学技术处、社会科学处)

  • 2017-12-31 吉林省自然科学学术成果奖三等奖

教学信息 (数据来源:教务处)

  • web程序设计实践
  • Web程序设计实践
  • 现代教育技术

科研信息 (数据来源:科学技术处、社会科学处)

  • 项目:
  • 1. 面向高维混合属性数据的聚类方法研究,2016年
  • 2. 混合属性条件下的聚类分析方法研究,2015年
  • 专著:
  • 1. 面向多维混合属性数据的聚类分析理论与算法,吉林大学出版社,01-8年
  • 论文:
  • 1. MRMD-Palm: A novel method for the identification of palmitoylated protein,CHEMOMETR INTELL LAB,2021年
  • 2. Clustering Mixed Numeric and Categorical Data With Cuckoo Search,IEEE ACCESS,2020年
  • 3. DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning,MATH BIOSCI ENG,2019年
  • 4. Analysis and prediction of human acetylation using a cascade classifier based on support vector machine,BMC BIOINFORMATICS,2019年
  • 5. Composite Feature Extraction and Selection for Text Classification,IEEE ACCESS,2019年
  • 6. Clustering mixed numeric and categorical data with artificial bee colony strategy,J INTELL FUZZY SYST,2019年
  • 7. Identifying N6 -methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer,J THEOR BIOL,2019年
  • 8. An Improved Binary Differential Evolution Algorithm for Feature Selection in Molecular Signatures,Molecular Informatics,2018年
  • 9. 基于模糊质心的混合属性数据模糊加权聚类算法,计算机科学,2018年
  • 10. Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network,J ELECTRON IMAGING,2017年
  • 11. A novel cluster center initialization method for the k-prototypes algorithms using centrality and distance,APPLIED MATHEMATICS & INFORMATION SCIENCES,2015年
  • 12. An initialization method for clustering mixed numeric and categorical data based on the density and distance,INT J PATTERN RECOGN,2015年
  • 13. A novel artificial bee colony based clustering algorithm for categorical data,PLoS ONE ,2015年
  • 14. Positive, negative and mixed-type solutions for periodic vector differential equations,ROCKY MT J MATH,2014年
信息维护