机构

• 自动化研究所 [2]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2022 [1]
• 2021 [1]
• 2010 [1]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 SE-GRU: Structure Embedded Gated Recurrent Unit Neural Networks for Temporal Link Prediction 期刊论文  OAI收割 IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2022, 卷号: 9, 期号: 4, 页码: 2495-2509 作者:  Yin, Yanting;  Wu, Yajing;  Yang, Xuebing;  Zhang, Wensheng;  Yuan, Xiaojie   |  收藏  |  浏览/下载：52/0  |  提交时间：2022/07/25 Time-frequency analysis  Feature extraction  Predictive models  Optimization  Topology  Measurement  Logic gates  Temporal link prediction  dynamic graphs  graph embedding  neural networks   Topology Prediction and Structural Controllability Analysis of Complex Networks Without Connection Information 期刊论文  OAI收割 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 13 作者:  Yang, Dongsheng;  Sun, Yunhe;  Wei, Qinglai;  Zhang, Huaguang;  Li, Ting   |  收藏  |  浏览/下载：31/0  |  提交时间：2022/01/27 Controllability  Topology  Complex networks  Sun  Pattern matching  Couplings  Web sites  Complex networks  structural controllability  topology prediction   The costs prediction of AOD furnace based on improved RBF neural network (EI CONFERENCE) 会议论文  OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China Na T.; Zhang D.-J.; Hui L. 收藏  |  浏览/下载：17/0  |  提交时间：2013/03/25 In order to predict the cost  a model of cost prediction was set up based on adaptive hierarchical genetic algorithm and RBF neural network. Hierarchical genetic algorithm could optimize the topology and the parameters simultaneously. Compared with simple genetic algorithm  it has more efficiency in not only accelerating and stabilizing the parameters training but also determining the structure of the network. Adaptive crossover and mutation probability could accelerate the speed and avoid prematurity. The model was tested by five samples. The results showed that the prediction model has high prediction accuracy  which indicated that it was applicable to predict the cost by the model. 2010 IEEE.