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A new model and improvement on test methods of the readout noise in the CCD camera 会议论文
7th international symposium on precision engineering measurements and instrumentation, lijiang, china, august 7, 2011 - august 11, 2011
YangZuoting; RuanPing; GeWei; WangHong
收藏  |  浏览/下载:21/0  |  提交时间:2012/07/10
Contrast Study on Prediction Models of the Post-construction Settlement of Embankment in Saline Soil Area 会议论文
Jinan, PEOPLES R CHINA, OCT 14-16, 2011
作者:  Lai, TW;  Zhou, QY;  Lai, TW (reprint author), Lanzhou Univ, Sch Civil Engn & Mech, Lanzhou 730000, Gansu, Peoples R China.
收藏  |  浏览/下载:1/0  |  提交时间:2017/01/18
Studies on wave field of extracorporeal focused shock wave therapy system 会议论文
2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011, Shanghai, China, October 15, 2011 - October 17, 2011
作者:  Wang, Wei;  Hu, Lintao;  Deng, Yun;  Wang, Na;  Sun, Jian
收藏  |  浏览/下载:3/0  |  提交时间:2017/01/18
Modified residual control charts for processes with changing variances 会议论文
23rd Chinese Control and Decision Conference, MAY 23-25, 2011
作者:  Sun, Qiuxia;  Zhao, Jianli;  Gao, Qisheng
收藏  |  浏览/下载:1/0  |  提交时间:2019/12/31
Provably secure identity based signature without trusted PKG in the standard model 会议论文
作者:  Peng, Wei;  Feng, Tao
收藏  |  浏览/下载:8/0  |  提交时间:2020/11/15
Prediction of concrete strength using fuzzy neural networks 会议论文
Haikou, China, June 18, 2011 - June 20, 2011
作者:  Xu, Jing;  Wang, Xiuli
收藏  |  浏览/下载:4/0  |  提交时间:2020/11/15
Algebra  Building materials  Civil engineering  Compressive strength  Construction equipment  Forecasting  Fuzzy inference  Fuzzy logic  Fuzzy systems  Learning algorithms  Least squares approximations  Mathematical models  Network architecture  Adaptive neuro-fuzzy inference system  Automatic-learning  Average relative error  Compressive strength of concrete  Concrete strength  Concrete strength prediction  Condition parameters  Expert experience  Fuzzy logic inference  Fuzzy Neural Networks (FNN)  Gradient Descent method  Hybrid-learning algorithm  Input and outputs  Input-output data  Intelligent prediction  Least squares methods  Parameter set  Power functions  Practical engineering  Prediction model  Rebound value  Relative standard error  Specific equations  Strength values  Takagi-sugeno  Test results  Training patterns  


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