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	A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems 期刊论文 OAI收割 SUSTAINABILITY, 2021, 卷号: 13, 期号: 19, 页码: 27 作者: Lodhi, Ehtisham; Wang, Fei-Yue; Xiong, Gang; Mallah, Ghulam Ali; Javed, Muhammad Yaqoob \| 收藏 \| 浏览/下载：29/0 \| 提交时间：2022/01/27 photovoltaic (PV) partial shading maximum power point tracking (MPPT) dragonfly optimization algorithm (DOA) adaptive cuckoo search optimization (ACSO) fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN) improved particle swarm optimization (IPSO) voltage source inverter (VSI) total harmonic distortion (THD)
	New methods for prediction of elastic constants based on density functional theory combined with machine learning 期刊论文 OAI收割 COMPUTATIONAL MATERIALS SCIENCE, 2017, 卷号: 138, 页码: 135-148 作者: Wang, Juan; Yang, Xiaoyu; Zeng, Zhi; Zhang, Xiaoli; Zhao, Xushan \| 收藏 \| 浏览/下载：35/0 \| 提交时间：2018/08/16 Prediction Of Elastic Constants Materials Informatics Dft Calculation Neural Network General Regression Neural Network Support Vector Regression
	酱油种曲培养过程的控制、建模与优化学位论文 OAI收割工程硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2012 张如意收藏 \| 浏览/下载：68/0 \| 提交时间：2015/09/02 酱油种曲控制系统广义回归神经网络粒子群优化 Seed Koji of Soy Sauce Control System General Regression Neural Network Particle Swarm Optimization
	Tracking error estimate for theodolite based on general regression neural network (EI CONFERENCE) 会议论文 OAI收割 3rd international Conference on Manufacturing Science and Engineering, ICMSE 2012, March 27, 2012 - March 29, 2012, Xiamen, China 作者: Li M. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 To efficiently evaluate the tracking index of theodolite as well as avoiding influence resulted from higher harmonics when used opto dynamic target and use equivalent sine to evaluate the tracking index in this paper we resorted to General Regression Neural Network to do the new research on theodolite tracking accuracy evaluation method. Experimental results indicate that the method realized the equivalent sine to evaluate the tracking index of theodolite and avoided the higher harmonics influence with opto dynamic target. The research in this paper has important value to the engineering practice. (2012) Trans Tech Publications.
	Tracking error modeling of the theodolite based on GRNN method (EI CONFERENCE) 会议论文 OAI收割 2nd International Conference on Frontiers of Manufacturing and Design Science, ICFMD 2011, December 11, 2011 - December 13, 2011, Taichung, Taiwan 作者: Li M. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 To meet the requirement of high tracking accuracy as well as develop more reasonable evaluation method in this paper the General Regression Neural Network (GRNN) has been applied to build the tracking error model of the theodolite. First we analyze the nonlinear factors in the theodolite. Second we discuss the principle of GRNN including its structure the function as well as its priors. Third we build the tracking error model based on GRNN and verify the model through the different parameters. The result indicated that the network model based on GRNN has high accuracy and good generalization ability. It could instead the real system to a certain extent. The research in this paper has important value to the engineering practice.
	Currency crisis forecasting with general regression neural networks 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2006, 卷号: 5, 期号: 3, 页码: 437-454 作者: Yu, Lean; Lai, Kin Keung; Wang, Shou-Yang \| 收藏 \| 浏览/下载：15/0 \| 提交时间：2018/07/30 currency crisis forecasting general regression neural network (GRNN) exchange rate volatility currency crisis early-warning system
	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：36/0 \| 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