scholarly journals Exploring the relationship between the dielectric properties and viability of human normal hepatic tissues from 10 Hz to 100 MHz based on grey relational analysis and BP neural network

2021 ◽  
pp. 104494
Author(s):  
Hang Wang ◽  
Lei Wang ◽  
Lin Yang ◽  
Xuetao Shi ◽  
Zhihong Wen ◽  
...  
Keyword(s):  
Neural Network ◽  
Dielectric Properties ◽  
Bp Neural Network ◽  
Grey Relational Analysis ◽  
Relational Analysis ◽  
Grey Relational ◽  
The Relationship

scholarly journals Optimization of sand casting performance parameters and missing data prediction

2019 ◽  
Vol 6 (8) ◽  
pp. 181860 ◽  
Author(s):  
Qingwei Xu ◽  
Kaili Xu ◽  
Li Li ◽  
Xiwen Yao
Keyword(s):  
Neural Network ◽  
Missing Data ◽  
Bp Neural Network ◽  
Grey Relational Analysis ◽  
Sand Casting ◽  
Performance Parameters ◽  
Relational Analysis ◽  
Data Prediction ◽  
Missing Data Prediction ◽  
Grey Relational

Due to a wide range of applications, sand casting occupies an important position in modern casting practice. The main purpose of this study was to optimize the performance parameters of sand casting based on grey relational analysis and predict the missing data using back propagation (BP) neural network. First, the influence of human factors was eliminated by adopting the objective entropy weight method, which also saved manpower. The larger variation degree in the evaluation indicators, indicating that the evaluated projects had good discrimination in this regard, the larger weight should be given to these evaluation indicators. Second, the performance parameters of sand casting were optimized based on grey relational analysis, providing a reference for sand milling. The larger the grey relational degree, the closer the evaluated project was to the ideal project. Third, this paper provided a new method for determining the number of hidden neurons in a network according to the mean square error of training samples, and venting quality was predicted based on BP neural network. The relevant theory was deduced before predicting missing data, such that there will be a general understanding regarding the prediction principle of BP neural network. Fourth, to demonstrate the validity of BP neural network adopted in the process of missing data prediction, grey system theory was applied to compare the result of missing data prediction.

scholarly journals Study on Prediction of Coal-Gas Compound Dynamic Disaster Based on GRA-PCA-BP Model

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kai Wang ◽  
Kangnan Li ◽  
Feng Du
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Coal Mine ◽  
Bp Neural Network ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Coal Gas ◽  
Relational Analysis ◽  
Dynamic Disaster ◽  
Grey Relational

The intensity and depth of China’s coal mining are increasing, and the risk of coal-gas compound dynamic disaster is prominent, which seriously restricts the green, safe, and efficient mining of China’s coal resources. How to accurately predict the risk of disasters is an important basis for disaster prevention and control. In this paper, the Pingdingshan No. 8 coal mine is taken as the research object, and the grey relational analysis (GRA), principal component analysis (PCA), and BP neural network are combined to predict the coal-gas compound dynamic disaster. First, the weights of 13 influencing factors are sorted and screened by grey relational analysis. Next, principal component analysis is carried out on the influencing factors with high weight value to extract common factors. Then, the common factor is used as the input parameter of BP neural network to train the previous data. Finally, the coal-gas compound dynamic disaster prediction model based on GRA-PCA-BP neural network is established. After verification, the model can effectively predict the occurrence of coal-gas compound dynamic disaster. The prediction results are consistent with the actual situation of the coal mine with high accuracy and practicality. This work is of great significance to ensure the safe and efficient production of deep mines.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

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