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	True triaxial test and PFC3D-GBM simulation study on mechanical properties and fracture evolution mechanisms of rock under high stresses 期刊论文 OAI收割 COMPUTERS AND GEOTECHNICS, 2023, 卷号: 154, 期号: -, 页码: - 作者: Zheng, Zhi; Tang, Hao; Zhang, Qiang; Pan, Pengzhi; Zhang, Xiwei \| 收藏 \| 浏览/下载：92/0 \| 提交时间：2023/08/02 True triaxial test 3D grain -based model Macro and micro -fracture characteristics Tensile -shear fracture mechanisms Fracture evolution processes B -value precursor analysis
	Comparing Estimation Methods for Soil Organic Carbon Storage in Small Karst Watersheds 期刊论文 OAI收割 Polish journal of environmental studies, 2018, 卷号: 27, 期号: 4, 页码: 1879-1890 作者: Zhenming Zhang; Yunchao Zhou; Shijie Wang; Xianfei Huang \| 收藏 \| 浏览/下载：37/0 \| 提交时间：2019/05/09 Estimation Method soil Organic Carbon Storage true Value small Watershed karst
	Research on the close noise field of the piezoelectric pump (EI CONFERENCE) 会议论文 OAI收割 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006, June 25, 2006 - June 28, 2006, Luoyang, China Jizhuang L.; Jianhui Z.; Shouyin W.; Qixiao X.; Desheng L. 收藏 \| 浏览/下载：59/0 \| 提交时间：2013/03/25 Restraining the noise meanwhile improving the dynamic characteristics of the driving power of piezoelectric pump effectively are the final purposes of doing research on the reciprocating and flexural vibration of the piezoelectric vibrator. However among many papers regarding piezoelectric pump there are very few papers about the research on the noise of piezoelectric pump. This is far less than the research on the application of the piezoelectric pump in other fields. In this paper the research on the flexural vibration deformation and vibration radiation noise of the piezoelectric vibrator are carried out. Firstly the vibration equations of the piezoelectric vibrator are built and flexural vibration deformation function is deduced. Then the simplified vibration model of the piezoelectric vibrator is introduced by using vibration theories of micro-area piston. Furthermore theoretical calculation equations of sound pressure in close noise field and noise contribution equation of fluid in pump are deduced. Finally a comparison is made between the theoretical calculation value and experimental value and the contribution quantities of the piezoelectric vibrator and fluid in pump are obtained respectively under different frequencies. The consequence approves that the theory introduced by this research is true. 2006 IEEE.
	Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Z.; Zhou F.; Wang C.; Li Z. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and Lab* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card XYZ value is gotten from the color luminance meter the training error is 0.000748566 it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value the color picture captured from CCD camera is expressed for RGB value as the input of neural network and the Lab* value converted from XYZ value is regarded as the real color value of target card which the difference is not obvious comparing with forecast result the maximum is 5.6357 NBS namely the output of neural network. The neural network of two hidden-layers is considered the minimum is 0.5311 NBS so the second general revolving combination design is introduced into optimizing the structure of neural network and the average of color difference is 3.1744 NBS. which can carry optimization through unifying project design data processing and the precision of regression equation. Their mathematics model of encoding space is gained and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm optimization solution is gotten and function value of the goal is 0.0007168. The neural network of the optimization solution is trained