Prediction of <scp>BP</scp> neural network and preliminary application for suppression of low‐temperature oxidation of coal stockpiles by pulverized coal covering

Wan, Yongzhou; Wu, Jiaxin; Chu, Ruizhi; Miao, Zhenyong; Fan, Lulu; Bai, Lei; Meng, Xiuxia

doi:10.1002/cjce.23860

Cited by 11 publications

(3 citation statements)

References 24 publications

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“…In order to better coordinate the relationship between urbanization and ecology in the Gansu region, based on the measurement of coupling coordination degree, the coordinated development of urbanization and ecology in the Gansu region of the Silk Road Economic Belt is predicted by using the BP neural network, which can provide more reference for the development of the Silk Road Economic Belt. e BP neural network structure is presented in Figure 1 [19][20][21][22].…”

Section: Structure Of Bp Neural Networkmentioning

confidence: 99%

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Luo

2022

Scientific Programming

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On the basis of the construction of urbanization and ecology index system, this study takes the core area of Silk Road Economic Belt, Gansu, as the research object and creates the coordination evaluation model between urbanization and ecological environment in Gansu; meanwhile, it uses BP neural network to predict the coordinated development of urbanization and ecology in Gansu Province. Finally, the aforesaid model is validated by means of empirical evidence. The results show that Gansu, in the Silk Road Economic Belt, has accelerated its urbanization level in the 10-year period from 2010 to 2019 in the context of the Belt and Road Initiative, especially in Jiayuguan and Lanzhou, mainly due to its industrialization-led urbanization； meanwhile, in terms of coupling degree, most of them are between 0.45 and 0.55, and most of them are out-of-frequency pro-disorder recession type, indicating that under the background of urbanization, the ecology of each city and prefecture in Gansu is also under great pressure. At the same time, through the forecast, Gansu is considered to be in the red light in 2019, as the endangered disorder recession B environmental lagging type, indicating that Lanzhou is facing great ecological pressure, but in general, the relationship between human and land is gradually developing in harmony.

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Section: Structure Of Bp Neural Networkmentioning

confidence: 99%

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Luo

2022

Scientific Programming

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“…At this stage, the research on the optimization of energy consumption structure in the process of regional economic development is mainly based on the research of the multidimensional classification method and the innovation of the regional economic liberalization development analysis model, while the research on the combination innovation with intelligent data analysis method and big data analysis technology is less [5]. Wang and other scholars have proved through experiments that the energy consumption demand data of different enterprises in different regions have different data peaks, and their structural optimization efficiency can be improved from the perspective of intelligent data analysis of energy consumption data [6].…”

Section: Related Workmentioning

confidence: 99%

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

2022

Wireless Communications and Mobile Computing

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At present, local regions have the problems of low optimization dimension and unbalanced supply side in the energy consumption structure in the process of economic development. Based on this, this paper studies the optimization method of the regional economic energy consumption structure based on big data and BP neural network analysis strategy and designs an intelligent extraction model of the regional economic energy consumption structure based on the BP neural network. According to the correlation and internal matching of energy consumption data involved in the process of economic development in different regions, the quantitative high-value analysis of regional economic energy consumption structure is realized, and the accuracy of the analysis results is analyzed by Newton Leibniz theory. The results show that the optimization model of regional economic energy consumption structure based on the BP neural network can effectively improve the application scope and data utilization of energy consumption structure, effectively complete the intelligent classification of energy consumption of different enterprises, and indirectly improve the energy utilization and matching efficiency of the regional economy.

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“…The normalization function uses premnmx to achieve the result between 0 and 1. After training and simulation [40], the data are denormalized (postmnmx) [41].…”

Section: Design Of the Bp Neural Networkmentioning

confidence: 99%

Optimization of 3D Printing Parameters on Deformation by BP Neural Network Algorithm

Liu

Ding

Tian

2022

Metals

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Traditional processing technology is not suitable for the requirements of advanced manufacturing due to the disadvantages of large repeated experiments, high cost, and low economic effect. As the latest additive technology, 3D printing technology has to deal with many issues such as process parameters and nonlinear mathematical models. A three-layer backpropagation (BP) artificial neural network with a Lavenberg–Marquardt algorithm was established to train the network and predict orthogonal experimental data. Additionally, the best combination of parameters of material deformations were predicted and verified by experiments. The results show that the predicted value obtained by the BP model is in good agreement with the experimental value curve, with a small relative error and a correlation coefficient of 0.99985. Moreover, the deformation errors of the printed model are not more than 3%. The incorporation of the BP neural network algorithm into the 3D printing process can, therefore, help cope with related problems, which is a future trend.

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Prediction of BP neural network and preliminary application for suppression of low‐temperature oxidation of coal stockpiles by pulverized coal covering

Cited by 11 publications

References 24 publications

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

Optimization of 3D Printing Parameters on Deformation by BP Neural Network Algorithm

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