中国科学院机构知识库网格系统: 检索

Analysis of the Fluid-Structure Coupling Characteristics of a High-Speed Train Passing through a Tunnel 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS, 2022
作者: Ji ZL(纪占玲); Liu Wen; Guo DL(郭迪龙); 杨国伟i; Mao, Jun

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收藏 | 浏览/下载：26/0 | 提交时间：2022/10/23

High-speed train fluid-structure coupling coupled aerodynamics and vehicle dynamics passing through a tunnel track irregularities

Effects of Running Speed on Coupling between Pantograph of High-Speed Train and Tunnel Based on Aerodynamics and Multi-Body Dynamics Coupling 期刊论文 OAI收割
APPLIED SCIENCES-BASEL, 2021, 卷号: 11, 期号: 21, 页码: 16
作者: Ji, Zhanling; Guo, Yi; Guo, Dilong; Yang, Guowei; Liu, Yubiao

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收藏 | 浏览/下载：43/0 | 提交时间：2022/01/12

coupling effect between pantograph and tunnel high-speed pantograph high-speed train running speed coupled aerodynamics and multi-body dynamics passing through a tunnel

Differences among among three types of tropical deep convective clusters observed from A-Train satellites 期刊论文 OAI收割
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER, 2018, 卷号: 217, 页码: 253-261
作者: Zheng, Jianyu; Liu, Dong; Wang, Zhien; Wang, Yingjian

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收藏 | 浏览/下载：18/0 | 提交时间：2019/12/10

Deep convective clusters Surface convective precipitation Ice water content A-Train satellite observation

Effect of morphology on the optical properties of soot aggregated with spheroidal monomers 期刊论文 OAI收割
Journal of Quantitative Spectroscopy and Radiative Transfer, 2016, 卷号: 168, 页码: 158-169
作者: Wu, Yu; Cheng, Tianhai; Zheng, Lijuan; Chen, Hao

收藏 | 浏览/下载：22/0 | 提交时间：2017/04/24

MULTIANGLE SPECTROPOLARIMETRIC IMAGER ANGLE PHOTOPOLARIMETRIC MEASUREMENTS BIDIRECTIONAL REFLECTANCE A-TRAIN VISIBLE-LIGHT VEGETATION AEROSOLS CANOPIES MISSION SOIL

Estimation of wetland vegetation LAI in the Poyang Lake area using GF-1 and Radarsat-2 Data 期刊论文 OAI收割
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves, 2016, 卷号: 35, 期号: 3, 页码: 332-340
作者: Xu, Tao; Liao, Jing-Juan; Shen, Guo-Zhuang; Wang, Juan; Yang, Xiao-Hui

收藏 | 浏览/下载：31/0 | 提交时间：2017/04/24

A-TRAIN ALGORITHM MISSION LAND

Double inverted pendulum control based on three-loop PID and improved BP neural network (EI CONFERENCE) 会议论文 OAI收割
2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China
作者: Fan Y.

收藏 | 浏览/下载：37/0 | 提交时间：2013/03/25

To deal with the defects of BP neural networks used in balance control of inverted pendulum such as longer train time and converging in partial minimum this article reaLizes the control of double inverted pendulum with improved BP algorithm of artificial neural networks(ANN) builds up a training model of test simulation and the BP network is 6-10-1 structure. Tansig function is used in hidden layer and PureLin function is used in output layer LM is used in training algorithm. The training data is acquried by three-loop PID algorithm. The model is learned and trained with Matlab calculating software and the simuLink simulation experiment results prove that improved BP algorithm for inverted pendulum control has higher precision better astringency and lower calculation. This algorithm has wide appLication on nonLinear control and robust control field in particular. 2011 IEEE.

Handwritten character recognition based on 13-point feature of skeleton and self-organizing competition network (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010, May 11, 2010 - May 12, 2010, Changsha, China
Zhong C.; Ding Y.; Fu J.

收藏 | 浏览/下载：40/0 | 提交时间：2013/03/25

This article is about the recognition for handwritten characters. Firstly we use some conventional methods to preprocess the images and introduce the 13-point feature of skeleton method to extract the data that containing feature of the handwritten character. Secondly we use the data to train the self-organizing competition network. In the end we test the net and conclude that this method has a good performance at handwritten character recognition. 2010 IEEE.

Prediction model of molten iron endpoint temperature in AOD furnace based on RBF neural network (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Logistics Systems and Intelligent Management, ICLSIM 2010, January 9, 2010 - January 10, 2010, Harbin, China
Ma H.-T.; You W.; Chen T.

收藏 | 浏览/下载：28/0 | 提交时间：2013/03/25

According to Jilin Ferroalloy Factory 10-ton AOD furnace actual smelting condition analyzes the impact factor of AOD furnace molten iron endpoint temperature by optimizing the neural network connection weights and structure design prediction model of molten iron endpoint temperature based on RBF neural network using LM algorithm and 50 furnaces actual production data to train the model and predicts another 50 furnaces molten iron temperature Result shows that prediction model of molten iron endpoint temperature based on RBF neural network has a high accuracy when the error of endpoint temperature is 12 C hit rate of temperature is 82.4%. 2010 IEEE.

Detection of low contrast targets based on lifting scheme wavelet transform (EI CONFERENCE) 会议论文 OAI收割
2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, August 9, 2009 - August 12, 2009, Changchun, China
作者: Chen X.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

This paper present a fast algorithm for detection of low contrast objects by using wavelet filters based on lifting scheme. The advantage is robust to noise. According Swelden's lifting wavelet filters are biorthogonal wavelet filters containing free parameters. We use reference image of targets to train the lifting terms so that the learnt wavelet filters have the features of targets. Then applying such filters to the images including targets taken from camera system. We can detect the locations where the high frequency components are almost the same as those of the target image. 2009 IEEE.

Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文 OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.; Ma D.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly we use frame grabber to capture the 4-bar target image data. Then according to image gray scale we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets along with known target visibility are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.