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For the current problems in the security situation of colliery equipment ,and based on non-linear relationship among the parameters of colliery equipment ,this paper presents a method for forecasting the safety of colliery equipment based on BP neural network.By using BP neural network in the colliery safety equipment monitoring and warning issues,we established a multi-index comprehensive monitoring...
According to the Characteristics of complex object system, a comprehensive evaluation model for complex object system is established based on fuzzy theory and artificial neural network. To realize the intelligence and the visualization of the evaluation process, an intelligent comprehensive evaluation software system with the help of Visual Basic, database technique and MATLAB toolbox is designed...
The crude oil demand is growing rapidly in China, driven by its rapid industrialization and motorization. China has already become the second-largest oil importer nation in the world, after the United States. The dynamic GM(1,1) model of grey theory is used to develop the dynamic GM(M,N) model to forecast the crude oil consumption and production in China. In order to improve the forecasting accuracy,...
In this paper, two modeling approaches (artificial neural network and regression model) are established and used to predict the fiber diameter of melt blowing nonwovens. By analyzing the results of the models, the effects of process parameters on fiber diameter can be predicted. The results demonstrated that the ANN model yields more accurate and stable predictions than regression model, which is...
This paper describes slide-bending formation of metallic sheet by using a neural network. The formation of parts made of very thin metallic sheets has become increasingly important miniaturizing industrial products, including electrical and mechanical devices. One of the authors proposed a new method called a slide-bending formation method for the bending of the metallic sheet. In this method, the...
Powder Metallurgy (P/M) involves multiple input and output which are non-linearly related for which statistical optimization methods are not suitable. These considerations lead to adoption of neural network (NN) for proper selection of P/M process parameter. In the present work, white cast iron powder is taken as the work material and NN approach is employed which allows specification of multiple...
Production quality in the food production supply chain is studied in this paper. The deficiency of quality monitoring existing in traceability systems is analyzed. An abnormality diagnosis algorithm, pre-warning method and pre-warning system are presented. The potential production abnormality of the logistics unit in the whole supply chain is diagnosed; a warning is generated; and decision support...
Because there were a lot of facts that affect the intensity of coal and gas outburst, a BP neural network model for forecasting the intensity was constructed. Aimed at the shortcoming of the BP neural network, such as the slow training speed, easy to be trapped into the local optimums, and the premature convergence of genetic algorithm (GA) BP neural network, a method to design the BP neural network...
This paper studies various training algorithms of BP neural network and proposes an improved conjugate gradient algorithm which combines conjugate gradient algorithm with inexact line search route based on generalized Curry principle. The proposed algorithm has global convergence, optimizes the learning steps using new line search rules and improves the convergence speed. The new algorithm is applied...
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