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浏览/检索结果: 共14条，第1-10条 帮助 限定条件 发表日期：2021    专题：数学与系统科学研究院    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Wind speed interval prediction model based on variational mode decomposition and multi-objective optimization 期刊论文 APPLIED SOFT COMPUTING, 2021, 卷号: 113, 页码: 15 作者:  Wang, Jianzhou;  Cheng, Zishu 收藏  |  浏览/下载：13/0  |  提交时间：2022/04/29 Interval prediction  Multi-objective optimization algorithm  Wind speed  Combined models   An Implicit Function-Based Adaptive Control Scheme for Noncanonical-Form Discrete-Time Neural-Network Systems 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2021, 卷号: 51, 期号: 12, 页码: 5728-5739 作者:  Zhang, Yanjun;  Tao, Gang;  Chen, Mou;  Chen, Wen;  Zhang, Zhengqiang 收藏  |  浏览/下载：11/0  |  提交时间：2022/04/02 Adaptive control  Uncertainty  Nonlinear systems  Adaptation models  Asymptotic stability  Stability analysis  Adaptive control  asymptotic output tracking  discrete time (DT)  implicit function  noncanonical form   A New Hybrid VMD-ICSS-BiGRU Approach for Gold Futures Price Forecasting and Algorithmic Trading 期刊论文 IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2021, 卷号: 8, 期号: 6, 页码: 1357-1368 作者:  Li, Yuze;  Wang, Shouyang;  Wei, Yunjie;  Zhu, Qing 收藏  |  浏览/下载：14/0  |  提交时间：2022/04/02 Gold  Forecasting  Autoregressive processes  Predictive models  Signal resolution  Deep learning  Mathematical model  Algorithmic trading  bidirectional gated recurrent unit (BiGRU)  gold futures price forecasting  variational mode decomposition (VMD)   STOCHASTIC TRUST-REGION METHODS WITH TRUST-REGION RADIUS DEPENDING ON PROBABILISTIC MODELS 期刊论文 JOURNAL OF COMPUTATIONAL MATHEMATICS, 2021, 页码: 41 作者:  Wang, Xiaoyu;  Yuan, Ya-xiang 收藏  |  浏览/下载：5/0  |  提交时间：2022/04/02 Trust-region methods  Stochastic optimization  Probabilistic models  Trust region radius  Global convergence   Simultaneous variable selection in regression analysis of multivariate interval-censored data 期刊论文 BIOMETRICS, 2021, 页码: 12 作者:  Sun, Liuquan;  Li, Shuwei;  Wang, Lianming;  Song, Xinyuan;  Sui, Xuemei 收藏  |  浏览/下载：13/0  |  提交时间：2022/04/02 EM algorithm  interval censoring  minimum information criterion  multivariate analysis  transformation models   Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Lan, Hui;  Liu, Ziquan;  Hsiao, Janet H.;  Yu, Dan;  Chan, Antoni B. 收藏  |  浏览/下载：11/0  |  提交时间：2022/04/02 Hidden Markov models  Bayes methods  Data models  Computational modeling  Mixture models  Clustering algorithms  Analytical models  Clustering  hidden Markov mixture model (H3M)  hierarchical EM  variational Bayesian (VB)   Online Active Learning for Drifting Data Streams 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Liu, Sanmin;  Xue, Shan;  Wu, Jia;  Zhou, Chuan;  Yang, Jian 收藏  |  浏览/下载：13/0  |  提交时间：2022/04/02 Labeling  Data models  Uncertainty  Biological system modeling  Computational modeling  Cognition  Adaptation models  Active learning  concept drift  data stream classification  online incremental learning   Evaluating Performances and Importance of Venture Capitals: A Complex Network Approach 期刊论文 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2021, 卷号: 68, 期号: 5, 页码: 2060-2068 作者:  Liu, Jiaqi;  Li, Xuerong;  Lu, Linyuan;  Dong, Jichang;  Lu, Jinhu 收藏  |  浏览/下载：17/0  |  提交时间：2021/10/26 Venture capital  Investment  Complex networks  Companies  Industries  Technological innovation  Data models  Venture capital  co-investment network  investment performance  investment behavior   Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Liu, Yixin;  Li, Zhao;  Pan, Shirui;  Gong, Chen;  Zhou, Chuan 收藏  |  浏览/下载：4/0  |  提交时间：2022/04/02 Anomaly detection  Task analysis  Graph neural networks  Unsupervised learning  Predictive models  Pattern matching  Training  Anomaly detection  attributed networks  contrastive self-supervised learning  graph neural networks (GNNs)  unsupervised learning   Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise 期刊论文 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 4, 页码: 1184-1196 作者:  Zhang, Chihao;  Zhang, Shihua 收藏  |  浏览/下载：106/0  |  提交时间：2021/04/26 Matrix decomposition  Bayes methods  Data integration  Inference algorithms  Data models  Data mining  Gaussian distribution  Bayesian methods  matrix decomposition  data integration  variational Bayesian inference  maximum a posterior