scholarly journals Investigating the Working Efficiency of Typical Work in High-Altitude Alpine Metal Mining Areas Based on a SeqGAN-GABP Mixed Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ning Hua ◽  
He Huang ◽  
Xinhong Zhang

Man-machine efficacy evaluations of typical work in the safe mining of high-altitude alpine metal mines are associated with fuzziness, multiple indexes, and large subjective components. This results in difficulties in the prediction of the typical work efficiency in high-altitude alpine metal mining areas. In this study, ergonomic theory was applied to establish the evaluation index system of typical work efficiency in high-altitude alpine metal mining areas by studying the cooperative relationship between operators, working machines, working environment, and design variables. First, we investigated the collaborative relationship between workers, operating machinery, operating environment, and design variables in order to establish the evaluation index system of typical work efficiency in high-altitude alpine metal mining areas. Second, principal component analysis (PCA) was integrated with the fusion entropy weight method to (i) analyze the coupling correlation and overlapping effects between the factors influencing efficiency at different altitudes and (ii) to determine the key influencing factors. Third, a model based on the sequence generative adversarial network genetic algorithm backpropagation (SeqGAN-GABP) hybrid algorithm was established to predict the trends in the operating efficiency of typical work types in high-altitude alpine metal mining areas. Finally, three high-altitude alpine metal mines in Xinjiang were selected as representative examples to verify the proposed framework by comparing it with other state-of the art models (multiple linear regression prediction model, backpropagation (BP) neural network model, and genetic algorithm back propagation (GA-BP) neural network model). Results determine the average relative error of each model as 2.74%, 1.97%, 1.29%, and 1.02%, respectively, indicating the greater accuracy of our proposed method in predicting the efficiency of typical work types in high-altitude alpine mining areas. This study can provide a scientific basis for the establishment of mining safety judgment standards in high-altitude alpine areas.

2014 ◽  
Vol 1030-1032 ◽  
pp. 2664-2667
Author(s):  
Xi Kang Yan ◽  
Jing Yu Wang

A new evaluation index system, which includes five dimensions is put forward to evaluate the competitiveness of construction subcontracting enterprise properly. Based on GA optimized BP neural network model,construction subcontracting enterprises’ competitiveness can be quantitative analysis systematically. Use of Matlab simulation analysis,research has shown that this system can well solve the problem of construction subcontracting enterprise competitiveness evaluation.


2011 ◽  
Vol 143-144 ◽  
pp. 312-316 ◽  
Author(s):  
Dao Guo Li ◽  
Zhong Yuan Zhou ◽  
Chen Yang

Based on the complexity of the evaluation index for supplier selection in green supply chain, this paper puts forward the evaluation index system in green supply chain and presents BP neural network model to select supplier with evaluation indexes as BP neural network's input and the outcome of DEA/AHP model as BP neural network's expected output. It can be proved that the model can effectively select suppliers in green supply chain by simulation experiment with LIINGO 9.0 and MATLAB7.0.


Author(s):  
Xiaoman Liu

According to the internal laws and development trends of the management and operation of local public utilities in China, the performance level of local public utility management in our country is predicted, and the corresponding performance evaluation index system is established. It is for the reform of the local public utilities management system in China and related policies. The adjustment has certain positive significance. This paper uses pattern discriminant analysis technology and BP neural network model to build a local public utility management performance prediction model and uses 11 regions in the east, middle, and west of the country as samples to predict the local public utility management performance.


2015 ◽  
Vol 719-720 ◽  
pp. 1297-1301
Author(s):  
Lei Bai ◽  
Xiao Xin Guo

Teaching quality evaluation plays a key role for universities to improve its teaching quality and becomes a hot spot research field for related researchers. In this paper, we established the evaluation model of teaching quality based on BP neural network. Firstly an evaluation index system of teaching quality is designed. Then, according to the system we design the structure of BP neural network, determine the parameters and give the algorithm description. Finally, we program and verify the validity of the model in MATLAB environment. The experimental results show that the model can evaluate teaching quality practically by the evaluation index.


2012 ◽  
Vol 170-173 ◽  
pp. 3436-3439
Author(s):  
Xiao Hui Hou ◽  
Lei Huang ◽  
Xue Fei Li

The scientific research achievements are evaluated based on the BP neural network method which is developed in this paper. According to the analysis and consult with the well-known experts, set up the evaluation index system of scientific research achievements, and based on it, the BP neural network model which is used to evaluate the scientific research achievements is established. Through an actual example, in order to improve the solution efficiency, use the Matlab software to solve the model and get the evaluation result of the scientific research achievements in the example. The evaluation result has high accuracy and could meet the basic actual needs. The evaluation method which is set up in this paper will benefit to our country's evaluation index system of the scientific research achievements and will promote the development of evaluation methods of the scientific research achievements.


2012 ◽  
Vol 546-547 ◽  
pp. 1090-1094
Author(s):  
Jian Sheng Hao ◽  
Qi Zhi Huang ◽  
Shu Dong Li

In this paper, the system engineering theory research logistical equipment safeguard ability assessment method, and established the equipment support of the evaluation index system, using BP neural network can to approximate any nonlinear system advantage, based on the BP neural network of logistics equipment support capability evaluation model for logistics equipment safeguard the ability to provide a new method. The simulation results show that this method can ensure objectivity.


2013 ◽  
Vol 368-370 ◽  
pp. 2050-2053
Author(s):  
Jian Wei Zhang ◽  
Dong Lu Ye ◽  
Guan Chan Ye ◽  
Jing Zhi Zhou

According to the status of the current engineering construction field in our country, in order to adapt to the requirements of engineering construction project risk evaluation, this paper discuss establishing a reasonable risk evalluation index system and a model of effective risk evaluation. By analyzing the advantages and disadvantages of the general model of risk evaluation, determine the risk evaluation model combined with BP neural network with AHP; secondly,establish a risk evaluation index system; once again,illustrate the method which represents the correlation between evaluation index system and the degree of risk; finally, establish a reasonable BP neural network model.Key Word:Evaluation index; Risk Evaluation ;AHP;BP Neural Network; Model Construction


2021 ◽  
Vol 2074 (1) ◽  
pp. 012091
Author(s):  
Chunjie Fang

Abstract In order to improve the innovation ability of enterprises and enhance international competitiveness, it is necessary to correctly analyze and evaluate the innovation ability of industrial clusters. Therefore, BP neural network is used to explain the innovation ability of industrial clusters, and the evaluation index system is established. By investigating industrial clusters and using it to provide references for the evaluation of industrial clusters’ innovation capabilities.


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