科研成果:
英文论文:
[1] Wang R.Z., Zhang X.S., Wang M.H.. A two-layer model with partial mapping: Unveiling the interplay between information dissemination and disease diffusion, Applied Mathematics and Computation, Volume 468, 2024,128507, https://doi.org/10.1016/j.amc.2023.128507. (JCR Q1,中科院一区TOP, IF: 4.0)
[2] Liu, F. , Zhang, X.S., and Liu, Q., "An Emotion-Aware Approach for Fake News Detection," in IEEE Transactions on Computational Social Systems, doi: 10.1109/TCSS.2023.3335269. (JCR Q1,中科院二区, IF: 5.0)
[3] Zhang, X.S., Ma, Y.L., Wang M.H. An ALBERT-based TextCNN-Hatt hybrid model enhanced with topic knowledge for sentiment analysis of sudden-onset disasters. Engineering Applications of Artificial Intelligence, Vol. 123, Part A, 2023, 106136. Online. https://doi.org/10.1016/j.engappai.2023.106136 (JCR Q1,中科院一区TOP, IF: 7.802)
[4] Zhang, X.S., Ma, Y.L., Wang M.H. An attention‐based Logistic‐CNN‐BiLSTM hybrid neural network for credit risk prediction of listed real estate enterprises. Expert Systems, e13299,2023. http://doi.org/10.1111/exsy.13299 (JCR Q2, IF: 2.812)
[5] Zhang, X.S. and Y. Wang, Industrial character recognition based on improved CRNN in complex environments. Computers in Industry, 2022. 142. https://doi.org/10.1016/j.compind.2022.103732 (JCR Q1,中科院一区TOP, IF: 11.245)
[6] Zhong, X., X.S. Zhang, and P. Zhang, Pipeline risk big data intelligent decision-making system based on machine learning and situation awareness. Neural Computing & Applications, 2022. 34(18): p. 15221-15239. (JCR Q2, IF: 5.102) https://doi.org/10.1007/s00521-021-06738-5
[7] Zhang, X.S. and T. Gao, Multi-head attention model for aspect level sentiment analysis. Journal of Intelligent & Fuzzy Systems, 2020. 38(1): p. 89-96. (JCR Q4, IF: 1.737)
[8] Zhang, X.S. and Z. Wang, A microcalcification cluster detection method based on deep learning and multi-scale feature fusion. Journal of Supercomputing, 2019. 75(9): p. 5808-5830. (JCR Q2, IF: 2.557)
[9] Zhang, X.S., T. Gao, and D. D. Gao, A new deep spatial transformer convolutional neural network for image saliency detection. Design Automation for Embedded Systems, 2018. 22(3): p. 243-256. (JCR Q3, IF: 3.815)
[10] Zhang, X.S. and X.B. Gao, Twin support vector machines and subspace learning methods for microcalcification clusters detection. Engineering Applications of Artificial Intelligence, 2012. 25(5): p. 1062-1072. (JCR Q1,中科院一区TOP, IF: 7.802)
中文论文:
[1]王润周(博士),张新生,王明虎.基于信号分解和深度学习的农产品价格预测[J].农业工程学报,2022,38(24):256-267.
[2]张新生,贺凯璐.基于SSA-CNN的长距离矿浆管道临界流速预测[J].安全与环境学报,2022,22(05):2524-2531.DOI:10.13637/j.issn.1009-6094.2021.0421.
[3]张新生,王旭业,张莹莹,常潆戈.海底腐蚀管道剩余寿命预测与维修策略研究[J].中国安全科学学报,2022,32(03):41-47.DOI:10.16265/j.cnki.issn1003-3033.2022.03.006.
[4]张新生,常潆戈.基于FA-BAS-ELM的海洋油气管道外腐蚀速率预测[J].中国安全科学学报,2022,32(02):99-106.DOI:10.16265/j.cnki.issn1003-3033.2022.02.014.
[5]张新生,蔡宝泉.基于改进随机森林模型的海底管道腐蚀预测[J].中国安全科学学报,2021,31(08):69-74.DOI:10.16265/j.cnki.issn1003-3033.2021.08.010.
[6]张新生,杨青.基于GMM-PNN模型的海底油气管道风险等级评价[J].安全与环境学报,2021,21(03):935-942.DOI:10.13637/j.issn.1009-6094.2019.1686.
[7]张新生,张莹莹.基于KPCA-ALO-WLSSVM的埋地管道外腐蚀速率预测[J].安全与环境学报,2022,22(04):1804-1812.DOI:10.13637/j.issn.1009-6094.2021.0275.
[8]张新生,张琪.基于改进RFFS和GSA-SVR的长输油管道腐蚀深度预测研究[J].系统工程理论与实践,2021,41(06):1598-1610.
[9]张新生,张平.不完全维修下海底腐蚀管道剩余寿命预测[J].系统工程理论与实践,2019,39(11):2984-2994.
[10]张新生,高腾.多头注意力记忆网络的对象级情感分类[J].模式识别与人工智能,2019,32(11):997-1005.DOI:10.16451/j.cnki.issn1003-6059.201911004.
[11]张新生,吕品品.考虑随机效应的腐蚀管道贝叶斯退化分析[J].中国安全科学学报,2019,29(08):73-80.DOI:10.16265/j.cnki.issn1003-3033.2019.08.012.
[12]张新生,王哲.基于EMICA-KRR的长输管道压力监测与泄漏定位方法[J].系统工程理论与实践,2019,39(07):1885-1895.
[13]张新生,叶晓艳.最优加权组合模型在管道腐蚀预测中的应用[J].中国安全生产科学技术,2019,15(05):68-73.
[14张新生,叶晓艳.不同初始条件的UGM(1,1)管道腐蚀预测建模研究[J].中国安全科学学报,2019,29(03):63-69.DOI:10.16265/j.cnki.issn1003-3033.2019.03.011.
[15]张新生,王哲.结合深度学习与特征多尺度融合的微钙化簇检测[J].模式识别与人工智能,2018,31(11):1028-1039.DOI:10.16451/j.cnki.issn1003-6059.201811007.
[16]高东东(研究生),张新生.基于空间卷积神经网络模型的图像显著性检测[J].计算机工程,2018,44(05):240-245.DOI:10.19678/j.issn.1000-3428.0048490.
[17]张新生,赵梦旭,王小完.尾段残差修正GM(1,1)模型在管道腐蚀预测中的应用[J].中国安全科学学报,2017,27(01):65-70.DOI:10.16265/j.cnki.issn1003-3033.2017.01.012.
[18]张新生,王太郎,薛羽桐.“一带一路”背景下提升西安陆港国际中转枢纽功能的路径探析[J].城市发展研究,2015,22(11):120-124.
[19]张新生,常晓云,蒋丽云,骆正山.盐穴地下储气库稳定性评价系统及其应用[J].天然气工业,2015,35(11):83-90.
[20]张新生,李亚云,王小完.腐蚀油气管道维修策略优化研究[J].中国安全科学学报,2015,25(11):81-86.DOI:10.16265/j.cnki.issn1003-3033.2015.11.014.
[21]张新生,曹乃宁,王小完.Gumbel分布的油气管道的剩余寿命预测[J].中国安全科学学报,2015,25(09):96-101.DOI:10.16265/j.cnki.issn1003-3033.2015.09.016.