CORC

在结果中检索

CORC

浏览/检索结果: 共8条，第1-8条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Attitude Estimation of Unmanned Aerial Vehicle Based on LSTM Neural NetWork 会议论文
Windsor, BRAZIL, 2018
作者:  Yaohua Liu;  Yimin Zhou;  Xiang Li
收藏  |  浏览/下载：35/0  |  提交时间：2019/01/31
A High Energy Efficient Reconfigurable Hybrid Neural Network Processor for Deep Learning Applications 会议论文
IEEE JOURNAL OF SOLID-STATE CIRCUITS, 2018-04-01
作者:  Yin, Shouyi;  Ouyang, Peng;  Tang, Shibin;  Tu, Fengbin;  Li, Xiudong
收藏  |  浏览/下载：8/0  |  提交时间：2019/12/30
Adaptive operation-space control of redundant manipulators with joint limits avoidance 会议论文
Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
作者:  Xu, Q.;  Sun, X.
收藏  |  浏览/下载：11/0  |  提交时间：2019/12/30
A Nearest Neighbor Searches(NNS) Algorithm for Fast Registration of 3D Point Clouds based on GPGPU 会议论文
作者:  Wu, Fangfang;  Wang, Fei;  Jiang, Peilin;  Zhao, Chen;  Cheng, Jianhua
收藏  |  浏览/下载：2/0  |  提交时间：2019/12/02
K-d tree  GPU  ICP  NNS  Registration  
Ultrahigh Responsivity UV/IR Photodetectors Based on Pure CuO Nanowires 会议论文
5th Nanoscience and Nanotechnology Symposium (NNS), Surabaya, INDONESIA, 2013-10-23
作者:  Ate, Abdelrahim;  Zhu, Huichao;  Quan, Xiaotong;  Cai, Haitao;  Wang, Xiaojiao
收藏  |  浏览/下载：4/0  |  提交时间：2019/12/09
High performance UV sensor based on individual ZnO nanowire and photoelectric properties of individual ZnO nanowire surface in different atmospheres 会议论文
5th Nanoscience and Nanotechnology Symposium (NNS), Surabaya, INDONESIA, 2013-10-23
作者:  Ate, Abdelrahim;  Zhu, Huichao;  Cai, Haitao;  Quan, Xiaotong;  Wang, Xiaojiao
收藏  |  浏览/下载：4/0  |  提交时间：2019/12/09
Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE) 会议论文
14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011, Washington, DC, United states
Dai Y.; Hu J.; Zhao D.; Zhu F.
收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25
Traffic congestion leads to problems like delays  decreasing flow rate  and higher fuel consumption. Consequently  keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus  computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper  a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.  
A Nonlinear Adaptive Control Approach for an Activated Sludge Process Using Neural Networks (CPCI-S收录) 会议论文
26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC)
作者:  Lin Mei-jin[1];  Luo Fei[1]
收藏  |  浏览/下载：0/0  |  提交时间：2019/04/12

©版权所有 ©2017 CSpace - Powered by CSpace