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Damage Assessment of Earthen Sites of the Ming Great Wall in Qinghai Province 期刊论文
Journal on Computing and Cultural Heritage, 2020, 卷号: 13, 期号: 2
作者:  Du, Yumin;  Chen, Wenwu;  Cui, Kai;  Zhang, Jingke;  Chen, Zhuo
收藏  |  浏览/下载：13/0  |  提交时间：2020/11/14
Aero-Engine Inlet Vane Structure Optimization for Anti-Icing with Hot Air Film Using Neural Network and Genetic Algorithm 期刊论文
SAE Technical Papers, 2019, 卷号: 2019-June
作者:  Liu, J.;  Ke, P.
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30
FORMATION OF THE MININSKY ELECTRONIC INFORMATION AND EDUCATION ENVIRONMENT OF UNIVERSITY AT THE FIRST STAGE OF IMPLEMENTATION OF THE PROJECT "DE. ELECTRONIC TRAINING AND ELECTRONIC OBRAZOVATELNAYA WEDNESDAY" 期刊论文
Вестник Мининского университета, 2015, 卷号: Vol.0 No.3
作者:  A.V.Gushchin;  O.N.Prokhorova
收藏  |  浏览/下载：1/0  |  提交时间：2019/12/30
Reality Sim: A realistic environment for robot simulation platform of humanoid robot (EI CONFERENCE) 会议论文
5th International Conference on Automation, Robotics and Applications, ICARA 2011, December 6, 2011 - December 8, 2011, Wellington, New zealand
Fu Y.; Moballegh H.; Rojas R.; Jin L.
收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25
As a virtual training  testing and evaluating environment  simulation platform becomes a significant component in Soccer Robot project. Nevertheless  the simulated environment in a simulation platform usually has a big gap with the realistic world. In order to solve this issue  we demonstrate a more realistic simulation system which is called Reality Sim with numerous real images. By this system  the computer vision code could be easily tested on simulation platform. For this purpose  previously  an image database with a large quantity of images recorded by camera pose is built. Furthermore  if the camera pose of an image is not included in the database  an interpolation algorithm is used to reconstruct a brand-new realistic image of that pose such that a realistic image could be provided on every robot camera pose. Our results show this system effectively simulates a more realistic environment for simulation platform. 2011 IEEE.  
文本褒贬倾向判定系统的研究 期刊论文
2010, 2010
孟凡博; 蔡莲红; 陈斌; 吴鹏; MENG Fan-bo; CAI Lian-hong; CHEN Bin; WU Peng
收藏  |  浏览/下载：6/0
Self power-following test analysis on the 5 MW nuclear heating reactor with the ATHLET code 期刊论文
2010, 2010
Cao Wei; Zhou Zhiwei; Fang Jing
收藏  |  浏览/下载：5/0
Quantitative analysis method for MFL testing for oil and gas pipelines based on RBF neutral network 期刊论文
2010, 2010
Cui Wei; Huang Songling; Zhao Wei
收藏  |  浏览/下载：2/0
Computer simulation research on cognitive mechanism of human vision (EI CONFERENCE) 会议论文
International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2010, March 13, 2010 - March 14, 2010, Changsha, China
Ke H.; You W.
收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25
The development of intelligent system which accorded with human cognitive mechanism will exert a profound influence on national defense  economy  education  culture and etc. A computer simulation method according with cognitive mechanism of human vision was proposed on the basis of Structural Decomposition Theory. Many basic shape feature information tables of similar object from different side can determine a kind of object uniquely. System weighted basic shape features in two different information tables by membership degree and then calculated similarity. The identifying object which had the maximum similarity with it in system was what we needed. The system used 83 pictures of 6 kinds of objects with different side for training and testing. The experiment results demonstrated  task of basic shape extraction  object recognition and others can be completed effectively with the method in paper. The method in paper can be a new attempt on computer simulation method according with cognitive mechanism of human vision from cognitive field. 2010 Crown Copyright.  
Application of LS-SVM network in LDF forming process 期刊论文
Hanjie Xuebao/Transactions of the China Welding Institution, 2010, 卷号: 31, 期号: [db:dc_citation_issue], 页码: 9-12
作者:  Lu, Zhongliang;  Li, Dichen;  Lu, Bingheng;  Zhang, Anfeng
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/10
System identification of tracking error and evaluation of tracking performance using BP neural network (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, June 17, 2009 - June 19, 2009, Beijing, China
Zhang N.; Shen X.-H.
收藏  |  浏览/下载：14/0  |  提交时间：2013/03/25
A novel approach for evaluating the tracking performance of optoelectronic theodolite is proposed. First  an equivalent mathematic model of tracking error is established. Then  the equivalent sine signal is inputted to the equivalent model  and the outputs are sampled. The results of evaluating the tracking performance are obtained based on the statistical calculation of output produced by equivalent model. Equivalent model using the BP (Backprogration) neural network structure is identified. The training method of BP neural network adopts the LM (Levenberg-Marquardt) algorithm for the sake of speeding up training process. The BP neural network is trained and tested by using the training and testing samples gotten from the simulation model of optoelectronic theodolite tracking system under MATLAB/SIMULINK. The estimate errors of equivalent model including average error  maximum error and standard error are 2.5872e-0060  2.8 and 1.9. The results show that the equivalent model identified based on BP neural network meets the needs of evaluating the tracking performance of optoelectronic theodolite. The accurate evaluation of tracking performance is achieved. 2009 SPIE.  

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