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CAS IR Grid
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长春光学精密机械与物... [3]
过程工程研究所 [1]
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OAI收割 [4]
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会议论文 [3]
期刊论文 [1]
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2022 [1]
2011 [1]
2010 [2]
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Accurate Quantitative Analysis of Valuable Components in Zinc Leaching Residue Based on XRF and RBF Neural Network
期刊论文
OAI收割
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 2, 页码: 490-497
作者:
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收藏
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浏览/下载:39/0
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提交时间:2022/06/15
XRF
Accurate quantitative analysis
RBF neural network model
Zinc smelting leaching slag
Study of experimental design and Response Surface method for surrogate model of computational simulation (EI CONFERENCE)
会议论文
OAI收割
2nd Annual Conference on Electrical and Control Engineering, ICECE 2011, September 16, 2011 - September 18, 2011, Yichang, China
Xi R.
;
Jia H.
;
Xiao Q.
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浏览/下载:21/0
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提交时间:2013/03/25
While the high-precision simulation is widely used in science and technology
Design of Experiment (DOE) based on Response Surface (RS) method can be employed in surrogate model to reduce the cost and error. In order to illustrate the relationship between parameters and response features
several DOE methods and Response Surface (RS) method are studied. The author used polynomial regression and RBF neural network based on orthogonal array to build a rocket aerodynamic discipline surrogate model respectively which proved their feasibility. From the results of the test case
conclusion is drawn that characteristic as well as acclimatization of DOE methods and different approximation should be considered for different issues
so the factors of cost and accuracy could reach a balance synthetically. 2011 IEEE.
The costs prediction of AOD furnace based on improved RBF neural network (EI CONFERENCE)
会议论文
OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
Na T.
;
Zhang D.-J.
;
Hui L.
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浏览/下载:16/0
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提交时间:2013/03/25
In order to predict the cost
a model of cost prediction was set up based on adaptive hierarchical genetic algorithm and RBF neural network. Hierarchical genetic algorithm could optimize the topology and the parameters simultaneously. Compared with simple genetic algorithm
it has more efficiency in not only accelerating and stabilizing the parameters training but also determining the structure of the network. Adaptive crossover and mutation probability could accelerate the speed and avoid prematurity. The model was tested by five samples. The results showed that the prediction model has high prediction accuracy
which indicated that it was applicable to predict the cost by the model. 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.
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浏览/下载:25/0
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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.