部分学术论文:

2021-2026

1. Unsupervised progressive structural damage assessment using a denoising diffusion probabilistic model. Measurement, 2026, 262: 120074 (SCI, IF=5.6)

2. Multi-domain physics-based loss design for seismic response prediction. Computers and Structures, (SCI, IF=4.8), 2025, 319: 107979

3. TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data, Nature Communications（SCI, IF= 15.7）, 2025, 16: 3611

4. 长短期频域特征嵌入的建筑结构地震响应预测.  建筑结构学报, 2025, 46(11): 223-236,249

5. 结构地震响应预测大语言模型. 计算机工程与应用,2025,61(16):132-145

6. 解释纠偏框架：基于标准解释的归因分数生成方法，计算机学报，2025, 48(4): 949-970（EI，一级学报）

7. 融合扩增技术的无监督域适应方法，软件学报，2025, 36(07):3253-3270（EI，一级学报）

8.Pedestrian wind flow prediction using spatial-frequency generative adversarial network. Building Simulation, 2024, 17(2): 319-334 (SCI IF=6.1)

9. Transformer-based structural seismic response prediction, Structures, 2024, 61, 105929 (SCI IF=3.9)

10. Form-finding of tensegrity structures based on graph neural networks, Advances in Structural Engineering (SCI IF= 2.1), 2024, 27(15): 2664–2690

11. A gene regulatory network inference model based on pseudo‑siamese network, BMC Bioinformatics, 2023, 24:163 (SCI IF=3)

12. 融合空间偏好和语义的个体活动识别方法[J]. 国防科技大学学报,2022,44(3):57-66

13. 一种高层建筑群排布生成与推荐算法[J]. 南方建筑，2022（9）：96-106

14. 基于深度强化学习的多场景高层住宅自动布局方法。建筑科学，2022，38（12）：34-42，50

15. Ensemble learning-based hierarchical retrieval of similar cases for site planning, Journal of Computational Design and Engineering, 2021, 8(6): 1548-1561 (SCI IF= 1.251)

2020

1. Weakly supervised semantic segmentation by iterative superpixel-CRF refinement with initial clues guiding, Neurocomputing, 2020, 391: 25-41 (SCI. IF=4.438)

2. Identification of pan-cancer prognostic biomarkers through integration of multi-omics data. Frontiers in Bioengineering and Biotechnology, 2020, 8:268 (SCI, IF: 3.644)

3. Genetic variants detection based on weighted sparse group lasso. Frontiers in Genetics. 2020, 11:Article155 (SCI, IF:3.517)

4. A cancer survival prediction method based on graph convolutional network. IEEE Transactions on Nanobioscience, 2020, 19(1): 117-126（SCI, IF=1.927）

5. 基于显著图的弱监督实时目标检测。自动化学报，2020, 46(2): 242-255（EI，一级学报）

6. 基于对象位置线索的弱监督图像语义分割方法. 软件学报, 2020, 31(11): 3640-3656（EI，一级学报）

7. 改进选择策略的烟花算法，控制与决策，2020，35（2）：389-395

2019 

1. Variational inference with Gaussian mixture model and householder flow, Neural Networks, 2019, 109: 43–55（SCI, IF=5.785）

2. OutDet: an algorithm for extracting the outer surfaces of building information models for integration with geographic information systems. International Journal of Geographical Information Science, 2019, 33(7): 1444-1470（SCI, IF=3.545）

3. A new algorithm for identifying genome rearrangements in the mammalian evolution. Frontiers in Genetics, 2019, 10: 1020（SCI, IF=3.517）

4. Predicting MiRNA-disease association by latent feature extraction with positive samples. Genes, 2019, 10, 80: 1-14（SCI, IF=3.331）

5. Drug-target interaction data cluster analysis based on improving the density peaks clustering algorithm. Intelligent Data Analysis. 2019, 23(6): 1335-1353（SCI, IF=0.612）

6. Detecting transportation modes from GPS trajectories using recurrent neural network. 11th International Conference on Contemporary Problems of Architecture and Construction，438-446，Oct. 13-16, 2019, Yerevan, Armenia

7. 药物靶标作用关系预测结果评价及查询验证。计算机研究与发展，2019, 56(9): 1881-1888（EI，一级学报）

8. 基于深度学习的出行模式识别方法。哈尔滨工业大学学报，2019，51（11）：1-7（EI）

2018

1．An improved K-medoids algorithm based on step increasing and optimizing medoids. Expert Systems With Applications. 2018,92:464-473（JCR:Q1, ESI, SCI. IF= 3.928）

2．Weakly supervised semantic segmentation based on EM algorithm with localization clues. Neurocomputing. 2018, 275: 2574–2587（SCI, IF=3.317）

3. Gene-based nonparametric testing of interactions using distance correlation coefficient in case-control association studies. Genes, 2018, 9: 608 (SCI，IF=3.242)

4. Computational drug repositioning usingmeta-path-based semantic network analysis, BMC Systems Biology, 2018, 12(Suppl 9):134, 123-134 [From 29th International Conference on Genome Informatics Yunnan, China. 3-5 December 2018] (SCI, IF=2.213)

5. Identification and priorization of differentially expressed genes for time-series gene expression data. Frontiers of Computer Science. 2018, 12(4): 813-823 (SCI，IF=1.105；ESI；CCF 推荐期刊)

6. Figure-ground segmentation based on class-independent shape priors, Journal of Electronic Imaging, 2018, 27(1), 013018 (SCI, IF=0.780) 

7．Prediction of potential disease-associated microRNAs based on hidden conditional random field. Journal of Harbin Institute of Technology (New Series), 2018，25（1）：57-65（EI）

8.Multi-label answer aggregation based on joint matrix factorization, International Conference on Data Mining (ICDM) (CCF Rank B). pp. 517-526, Nov 17-20, 2018, Singapore（EI）

9.Weighted matrix factorization based data fusion for predicting lncRNA-disease associations, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2018, pp. 572-577, 3-6 December 2018, Madrid（EI）

10.基于U统计量和集成学习的基因互作检测方法，计算机研究与发展，2018，55 (8): 1683-1693（EI，一级学报）

11.水稻组织特异性蛋白质相互作用网络构建方法. 哈尔滨工业大学学报, 2018, 50(11): 1~9 (EI) 

2017

1．A comprehensive overview and evaluation of circular RNA detection tools. PLoS Computational Biology, 2017,13(6): e1005420 (SCI, IF=4.587) 

2．An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection. BMC Genomics, 2017, 18(Suppl 9):844[From IEEE BIBM International Conference on Bioinformatics & Biomedicine (BIBM) 2016,

Shenzhen, China. 15-18 December 2016]( SCI，IF=4.397)

3．A metric on the space of kth-order reduced phylogenetic networks. Scientific Reports, 2017, 7(1):3189（JCR:Q2, SCI. IF=4.259）

4. Refine gene functional similarity network based on interaction networks. BMC Bioinformatics, 2017, 18(Suppl 16):550, 183-193[From 16th International Conference on Bioinformatics (InCoB 2017) Shenzhen, China. 20-22 September 2017, the Graduate School at Shenzhen, Tsinghua University, China]（SCI，IF=2.448）

5．Constructing an integrated gene similarity network for the identification of disease genes. Journal of Biomedical Semantics 2017, 8(Suppl 1):32[From Biological Ontologies and Knowledge bases workshop on IEEE BIBM 2016 Shenzhen, China. 16 December 2016](SCI, IF=1.826)

6. Revealing protein functions based on relationships of interacting proteins and GO terms. Journal of Biomedical Semantics 2017, 8(Suppl 1):27, 9-17[From Biological Ontologies and Knowledge bases workshop on IEEE BIBM 2016, Shenzhen, China. 16 December 2016] (SCI, IF=1.826)

7．一种基于多组学生物网络的癌症关键模块挖掘方法. 中国科学: 信息科学， 2017, 47（11）: 1510-1522（EI，一级学报）

8．基于降维的蛋白质不相关功能预测. 中国科学: 信息科学，2017, 47（10）: 1349-1368（EI，一级学报）

9．基于距离不等式的K-medoids 聚类算法. 软件学报，2017,28(12):3115-3128（EI，一级学报）

10．miRNA与疾病关联关系预测算法. 软件学报，2017,28(11):3094-3102（EI，一级学报）

11．基于标记与特征依赖最大化的弱标记集成分类. 软件学报，2017, 28(11): 2851-2864（EI，一级学报）

12．基于读分割最优匹配的indels识别算法. 软件学报，2017, 28(10): 2640-2653（EI，一级学报）

2016 

1. Identify bilayer modules via pseudo-3D clustering: applications to miRNA-gene bilayer networks, Nucleic Acids Research, 2016, 44(20):e152(SCI, IF=10.162)

2. eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform. Scientific Reports, 2016，6, 30595; doi: 10.1038/srep30595 (SCI, IF=5.228) 

3. SGFSC: speeding the gene functional similarity calculation based on hash tables. BMC Bioinformatics. 2016, 17:445(SCI, IF=2.435) 

4. A robust local sparse coding method for image classification with Histogram Intersection Kernel. Neurocomputing, 2016, 184: 36–42 (SCI, IF=2.005) 

5. MiRTDL: a deep learning approach for miRNA target prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics(TCBB), 2016, 16(3): 1161-1169 (SCI, IF=1.955) 

6. EnPC: an ensemble clustering framework for detecting protein complexes in protein-protein interaction network, Current Proteomics, 2016, 13(2): 143-150(SCI, IF=0.59) 

7. Construct Protein-Protein Interaction Network based on domain-domain interactions. Journal of Harbin Institute of Technology(New Series), 2016, 23(4): 27-36(EI) 

8. Reconstructing gene regulatory network based on candidate auto selection method. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016(EI) 

9. Constructing an integrated gene similarity network for the identification of disease genes. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016(EI) 

10. Epistasis detection using a permutation-based gradient boosting machine. In the Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016). Shenzhen, China, 2016:1-6(EI) 

11. 基于正负样例的蛋白质功能预测. 计算机研究与发展. 2016, 53 (8): 1753-1765 (EI) 

12. 动态-静态混合的时序蛋白质网络构建方法. 哈尔滨工业大学学报. 2016,48(11):41-46(EI) 

2015 

1. HAlign: Fast multiple similar DNA/RNA sequence alignment based on the centre star strategy. Bioinformatics, 2015, 31(15): 2475-2481 (SCI, IF=4.981) 

2. A gene-based information gain method for detecting gene-gene interactions in case-control studies. European Journal of Human Genetics, 2015, 23: 1566-1572 (SCI, IF=4.349) 

3. SeedsGraph: an efficient assembler for next generation sequencing data. BMC Medical Genomics, 2015, 8(Suppl 2): S13 (SCI, IF=3.91) 

4. An overview of SNP interactions in genome-wide association studies. Briefings in Functional Genomics. 2015, 14(2): 143-155 (SCI, IF=3.427) 

5. Integrating multiple networks for protein function prediction, BMC Systems Biology, 2015, 9(Suppl 1): S3(SCI, IF=2.853) 

6. Harmonious competition learning for Gaussian mixtures. Neurocomputing, 2015, 170: 228-239(SCI, IF=2.005) 

7. Actively constructing an effective training set by expected gain maximization criterion. Neurocomputing, 2015, 158: 62-72(SCI, IF=2.005) 

8. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information. FEBS Open Bio, 2015, 5: 251-256(SCI, IF=1.515) 

9. 非负局部约束线性编码图像分类算法. 自动化学报, 2015, 41(7): 1235-1243(EI) 

10. 基于加性噪声模型的基因调控网络构建算法[J]. 哈尔滨工业大学学报, 2015, 47(11)：22-26(EI) 

11. 基于信息增益理论的整体基因中基因互作挖掘方法. 中国科技论文. 2015, 10(2)：186-191 

2014 

1. Inferring the soybean (Glycine max) microRNA functional network based on target gene network. Bioinformatics, 2014, 30(1): 94-103 (SCI, IF=5.323) 

2. SoyFN: a knowledge database of soybean functional networks. DATABASE - The Journal of Biological Databases and Curation(Oxford), 2014: bau019 (SCI, IF=4.200) 

3. A least square method based model for identifying protein complexes in protein-protein interaction network. BioMed Research International, 2014, 720960:1-9(SCI, IF:2.706) 

4. Computational prediction of protein function based on weighted mapping of domains and GO terms. BioMed Research International, 2014, 641469: 1-9 (SCI, IF=2.706) 

5. CPL: Detecting protein Complexes by Propagating Labels on protein-protein interaction network. Journal of Computer Science and Technology, 2014, 29(6): 1083-1093(SCI, IF=0.642) 

6. Identification of functional miRNA regulatory modules and their associations via dynamic miRNA regulatory function. BIBM 2014 

7. 一种蛋白质复合体模块度函数及其识别算法. 计算机研究与发展. 2014, 51(10): 2178-2186(EI) 

8. SVM与主动学习方法相结合的蛋白质相互作用预测. 计算机科学, 2014, 41(2): 82-86 

2013 

1. LNETWORK: an efficient and effective method for constructing phylogenetic networks. Bioinformatics, 2013, 29(18): 2269-2276 (SCI, IF=5.323) 

2. Measuring gene functional similarity based on group-wise comparison of GO terms. Bioinformatics, 2013, 29(11): 1424-1432 (SCI, IF=5.323) 

3. Prediction of microRNAs associated with human diseases based on weighted k most similar neighbors. PLoS ONE, 2013, 8(8) : e70204 (SCI, IF=4.411) 

4. A novel insight into gene ontology semantic similarity. Genomics, 2013, 101(6): 368-375 (SCI, IF=2.958) 

5. Computational approaches on detecting non-coding RNA. Current Genomics. 2013, 14(6): 371-377(SCI, IF=2.408) 

6. BIMLR: A method for constructing rooted phylogenetic networks from rooted phylogenetic trees, Gene, 2013, 527(Issue 1): 344-351 (SCI, IF=2.196) 

7. A probabilistic model of active learning with multiple noisy oracles. Neurocomputing, 2013, 118: 253-262 (SCI, IF=1.634) 

8. MLPA: Detecting overlapping communities by multi-label propagation approach, accepted 2013 IEEE Congress on Evolutionary Computation(IEEE CEC 2013), June 20-23, Cancún, México: 681-688(EI) 

9. Effective constructing training sets for object detection. 2013 IEEE International Conference on Image Processing. Sep. 15-18, 2013, Melbourne, Australia: 3377-3380 (EI) 

10. A new distance computing method for DNA sequences in phylogenetic analysis. 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2013), July 23-25, 2013, Shenyang, China: 713-717(EI) 

2012 

1. Understanding microRNA regulation: A computational perspective. IEEE Signal Processing Magazine, 2012, 29(1):77-88(SCI, IF=5.86) 

2. A Bayesian decision fusion approach for microRNA target prediction．BMC Genomics, 2012, 13(Suppl 8):S13: 1-11(SCI, IF=4.397) 

3. Feature selection for monotonic classification. IEEE Transactions on Fuzzy Systems, 2012, 20(1): 69-81(SCI, IF=3.34) 

4. A new relational Tri-training system with adaptive data editing for inductive logic programming. Knowledge-Based Systems, 2012, 35(11): 173-185(SCI, IF=2.422) 

5. DBGSA: a novel method of distance-based gene set analysis. Journal of Human Genetics, 2012,57(10)：642-653(SCI, IF=2.4) 

6. Rank entropy-based decision trees for monotonic classification．IEEE Transactions on Knowledge and Data Engineering, 2012, 24(11): 2052-2064(SCI, IF=1.657) 

7. 基于采样策略的主动学习算法研究进展. 计算机研究与发展. 2012, 49(6): 1162?1173(EI) 

8. 植物抗性基因识别中的随机森林分类方法. 计算机科学与探索. 2012, 6(1): 67-77 

9. 关系tri-training: 利用无标记数据学习一阶规则. 计算机科学与探索, 2012, 6(5): 430-442 

2011 

1. PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs. Bioinformatics, 2011, 27 (10): 1368-1376(SCI, IF=5.323) 

2. MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. PLoS ONE, 2011, 6(11): e27422(SCI, IF=4.411) 

3. QTL underlying resistance to two HG types of Heterodera glycines found in soybean cultivar 'L-10'. BMC Genomics 2011, 12:233(SCI, IF=4.397) 

4. A new co-training-style random forest for computer aided diagnosis. Journal of Intelligent Information Systems, 2011, 36(3): 253-281(SCI, IF=0.875) 

5. Tri-training and MapReduce-based massive data learning. International Journal of General Systems, 2011, 40(4): 355-380(SCI, IF=0.826) 

2010 

1. Simple sequence-based kernels do not predict protein-protein interactions. Bioinformatics, 2010, 26(20): 2610-2614(SCI, IF=5.323) 

2. Fuzzy preference based rough sets. Information Sciences, 2010, 180(10): 2003-2022(SCI, IF=3.291；EI) 

3. Information entropy for ordinal classification. Science in China Series F-Information Sciences. 2010, 53(6): 1188-1200(SCI) 

4. DuplexFinder: Predicting the miRNA-miRNA* duplex from the animal precursors. Int. J. Bioinformatics Research and Applications, 2010, 6 (1): 69-81 

6. Genomic analysis of microRNA promoters and their cis-acting elements in soybean. Agricultural Sciences in China, 2010, 9(11): 1561-1570(SCI) 

8. Two-stage clustering based effective sample selection for classification of premiRNAs. IEEE International Conference on Bioinformatics & Biomedicine 2010 (IEEE BIBM 2010), 18-21 Dec 2010, Hong Kong 

9. 类别不平衡的分类方法及在生物信息学中的应用. 计算机研究与发展, 2010, 47(8): 1407-1414(EI) 

10. 多序列比对算法的研究进展. 生物信息学, 2010, 8(4)：311-315 

2009 

1. A hybrid clustering and graph based algorithm for tagSNP selection. Soft Computing, 2009,13(12):1143-1151(SCI, IF=1.328；EI) 

3. A site-clustering graph based tagSNP selection algorithm in genotype data. BMC Bioinformatics, 2009, 10 (Suppl 1):S71-82(SCI, IF=3.78；EI) 

3. Predicting RNA secondary structure based on the class information and Hopfield network. Computers in Biology and Medicine. 2009,39(3):206-214(SCI, IF=1.27；EI) 

4. Sea battle-filed simulation based on Vega. Journal of Harbin Institute of Technology, 2009, 16(1): 1-4(EI) 

5. Novel H/ACA box snoRNA Mining and Secondary Structure Prediction Algorithms. The 4th International Conference on Rough Sets and Knowledge Technology (RSKT2009), Gold Coast, Australia, 14th-16th July, 2009. LNAI, 5589: 538-546(EI, ISTP) 

6. 一种快速的多序列星比对算法. 电子学报, 2009,37(8): 1746-1750(EI) 

7. 基于直推式支持向量机的图像检索研究. 模式识别与人工智能, 2009, 22(5)：774-779 (EI) 

8. 质心法：受类别驱动的RNA二级结构预测方法. 南京大学学报. 2009, 45(5): 677-688 

9. 生物信息学中的学习问题. 山东大学学报. 2009, 39(3):1-6 

10. 基于线粒体SNP的疾病人群分类方法研究. 2009中国计算机大会.CNCC 2009 

11. 一种适合大豆MicroRNA鉴定的RT-PCR方法. 大豆科学, 2009, 28(4)：600-604 

2008 

1. A topological transformation in evolutionary tree search methods based on maximum likelihood combining p-ECR and neighbor joining. BMC bioinformatics, 2008, 9(Suppl 6):S4(SCI, IF=3.78；EI) 

2. A new approach to evolutionary tree reconstruction combining particle swarm optimization with p-ECR. International Journal of Computational Intelligence Research(Special issue on Particle swarm optimization), 2008, 4(2): 187-195 

3. Research on machine learning model and algorithm based on human cognition. In Proceedings of 2008 International Conference on Advanced Intelligence (ICAI2008), Beijing, China, Oct,2008: 59-64 

4. TagSNPs selection using maximum density subgraph. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 128-132(EI, ISTP) 

5. Participatory learning based semi-supervised classification. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v4: 207-216(EI, ISTP) 

6. An improved diverse density algorithm for multiple overlapped instances. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v3: 88-91(EI, ISTP) 

7. Prediction of protein-protein interactions from secondary structures on binding motifs using the statistic method. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 100-103(EI, ISTP) 

8. A novel comparative sequence analysis method for ncRNA secondary structure prediction without multiple sequence alignment. In the 4 th International Conference on Natural Computation (ICNC'08, Oct.18-20, 2008), Jinan, China, v5: 29-33(EI, ISTP) 

9. 基于Tri-train ing和数据剪辑的半监督聚类算法. 软件学报, 2008, 19(3)：663-673(EI) 

10. 一种基于Quartet Puzzling 和邻接法的进化树构建算法. 计算机研究与发展, 2008, 45(11)：1965-1973(EI) 

11. RNA二级结构预测方法综述. 电子学报, 2008, 36(2)：331-337(EI) 

12. 基于智能Agent的农业智能决策系统研究. 高技术通讯, 2008, 18(4)：392-399(EI) 

13. 参数序列比对算法研究. 生物信息学, 2008, 6(2)：65-67, 84 

2007 

1. RNA secondary structure prediction based on forest representation and Genetic Algorithm. In The 3rd International Conference on Natural Computation (ICNC'07), 2007: 370-374(EI) 

2. An improved quick algorithm for aligning DNA/RNA sequences. CIS Workshops 2007, 2007 International Conference on Computational Intelligence and Security, Dec 15-19, 2007 Harbin, China: 825-828(EI, ISTP) 

3. 基于自适应数据剪辑策略的Tri-training算法. 计算机学报, 2007, 30(8)：1213-1226(EI) 

4. 转录因子结合位点识别算法的研究. 电子学报, 2007, 35(12A)：83-89(EI) 

5. 蛋白质相互作用及其网络预测方法研究进展. 电子学报, 2007, 35(12A)：1-7(EI) 

6. 基于支持向量机和竞争学习的图像配准方法. 哈尔滨工业大学学报, 2007, 39(7)：1114-1116(EI) 

2006 

1. Research of immune system response simulation based on cell automata. Chinese Journal of Electronics, 2006, 15(4A): 785-788 (SCI, EI) 

2. Tri-training and data editing based semi-supervised clustering algorithm. In 5th Mexican InternationalConferenceon Artificial Intelligence (MICAI 2006), Lecture Notes in Artificial Intelligence, 2006, Volume 4293: 641-651(EI, ISTP) 

3. A permutation-based genetic algorithm for predicting RNA secondary structure-a practicable approach,” The 2nd International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Lecture Notes in Artificial Intelligence (LNAI) 3614. 2006, 861-864(SCI, EI, ISTP) 

4. An ontology-based method for similarity calculation of concepts in the semantic web. 5th International Conference on Machine Learning and Cybernetics, AUG 13-16, 2006 .Proceedings of 2006 International Conference on Machine Learning and Cybernetics, Vols 1-7 : 1538-1542, 2006(EI, ISTP) 

5. 系统发生树构建技术综述. 电子学报, 2006, 34(11)：2047-2052(EI) 

6. 基于熟人联盟及扩充合同网协议的多智能体协商模型. 计算机研究与发展, 2006, 43(7)：1155-1160(EI) 

2005 

1. Improving retrieval performance with the combination of thesauri. and automatic relevance feedback. Advances in Machine Learning and Cybernetics, Lecture Notes in Computer Science, 2005, Volume 3930: 322-328(SCI, EI, ISTP) 

2. Evaluation criteria on down-compatibility degree of fuzzy inference mechanism. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics (ICMLC2005), Guangzhou, 18-21 August 2005. page:2418-2423(EI, ISTP) 

3. The research and application of the self-learning expert system based on BP network. Proceedings of the Fourth International Conference on Machine Learning and Cybernetics (ICMLC2005), Guangzhou, 18-21 August 2005. page:4153-4157(EI, ISTP) 

4. Middleware-based expert system platform for agriculture production decisions. In Proceeding of the Third International Symposium on Intelligent Information Technology in Agriculture (ISIITA2005), Beijing, P. R. China, 2005 

5. 基于progressive多序列比对方法求解多序列比对得启发式算法. 生物信息学, 2005, 3(4)：171-174 

2004 

1. A new Q-learning algorithm based on the metropolis criterion. IEEE Transactions On Systems, Man, And Cybernetics—Part B: Cybernetics, 2004, 34 (5): 2140- 2143 (SCI, IF=2.36；EI) 

2. Q_learning based on active backup and memory mechanism. In Proceeding of the Third International Conference on Machine Learning and Cybernetics (ICMLC 2004), Shanghai, P. R. China, 2004: 271-275(EI, ISTP) 

3. 基于规则和模糊线性规划表示的专家系统研究. 高技术通讯, 2004, 14(7)：1- 4(EI) 

4. 一种快速的间接关联挖掘算法. 高技术通讯, 2004, 14(7)：49- 52(EI) 

5. 一种新的面向属性归纳中概念层次技术研究. 管理科学学报, 2004, 7(1)：65-72 

2003之前 

1. Application of nonlinear color matching model to four-color ink-jet printing. Journal of Harbin Institute of Technology (New Series). 2002, 9(3): 270-275(EI) 

2. A simulated annealing-based algorithm for traveling salesman problem. Journal of Harbin Institute of Technology (New Series). 1997, 4(4): 35-38(EI) 

3. Research on knowledge representation and inference based on extended weighted fuzzy logic. In Proceeding of the Second International Symposium on Intelligent Information Technology in Agriculture (ISIITA), Beijing, P. R. China, 2003: 95-98 

4. Research of dithering pattern based on evolutionary algorithm and space_filling curve. In Proceedings of 2001 International Conference on Management Science & Engineering, Harbin, P. R. China, 2001: 590-594(ISTP) 

5. 基于BP网络的色彩匹配方法研究. 计算机学报, 2000, 23(8)：819-823(EI) 

6. 评价函数驱动的抖动模式的研究.软件学报, 1998, 9(5)：383-389 (EI) 

7. 一种基于信息增益与费用评价函数的特征选择准则. 计算机研究与发展, 1999, 36(7)：788-793(EI) 

8. 基于样本空间学习算法的彩色匹配方法研究. 自动化学报, 2001, 27(2)：186-193(EI) 

9. 基于偏最小二乘回归分析的混色数据学习算法研究. 电子学报, 2001, 29(3)：429-431(EI) 

10. 基于划分策略和填充曲线的抖动模式研究. 计算机辅助设计与图形学学报, 2001, 13(4)：319-323(EI) 

11. 基于BACON系统实现彩色图像黑白打印方法的自动化. 计算机辅助设计与图形学学报, 2001, 13(8)：747-751(EI) 

12. 专家系统中知识库组织与维护技术的研究. 高技术通讯, 2002, 12(2)：1- 4, 9(EI) 

13. 加强学习中决策准则的选择. 清华大学学报, 1998, 38(S2)：165-168 

14. 题库系统试卷自动生成算法研究. 哈尔滨工业大学学报, 2003, 35(3)：342-346(EI) 

15. 一个新的基于扩张矩阵的规则抽取覆盖算法. 哈尔滨工业大学学报, 2000, 32(4)：123-126(EI) 

16. 连续属性空间的规则学习算法. 哈尔滨工业大学学报, 2000, 32(3)：42-47(EI) 

17. 示例学习的扩张图方法. 哈尔滨工业大学学报, 1998, 30(1)：65-67(EI) 

18. 基于机器学习的手写汉字特征选择. 哈尔滨工业大学学报, 1998(2), 30(1)：57-60(EI) 

19. 基于模拟退火算法的抖动模式的研究与实现. 哈尔滨工业大学学报, 1997, 29(3)：65-67(EI)

出版书籍：

[1]（美）卢格（Luger，G. F.）著；郭茂祖等译。人工智能：复杂问题求解的结构和策略（原书第6版），北京：机械工业出版社，2009. 12

[2]（英）罗杰斯（Rogers，S.），（英）吉罗拉米（Girolami，M.）著；郭茂祖等译。机器学习教程，北京：机械工业出版社，2013. 10