Extension prediction model of soft rock tunnel deformation grade based on entropy weight method and rough set

2021 ◽  
Vol 81 (1) ◽  
Author(s):  
Yiguo Xue ◽  
Haiting Liu ◽  
Chenghao Bai ◽  
Maoxin Su ◽  
Daohong Qiu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Rough Set ◽  
Soft Rock ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Rock Tunnel

scholarly journals Study on Development Sustainability of Atmospheric Environment in Northeast China by Rough Set and Entropy Weight Method

2019 ◽  
Vol 11 (14) ◽  
pp. 3793 ◽  
Author(s):  
Yuangang Li ◽  
Maohua Sun ◽  
Guanghui Yuan ◽  
Qi Zhou ◽  
Jinyue Liu
Keyword(s):  
Rough Set ◽  
Northeast China ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Atmospheric Environment ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Environment Sustainability

In order to evaluate the atmospheric environment sustainability in the provinces of Northeast China, this paper has constructed a comprehensive evaluation model based on the rough set and entropy weight methods. This paper first constructs a Pressure-State-Response (PSR) model with a pressure layer, state layer and response layer, as well as an atmospheric environment evaluation system consisting of 17 indicators. Then, this paper obtains the weight of different indicators by using the rough set method and conducts equal-width discrete analysis and clustering analysis by using SPSS software. This paper has found that different discrete methods will end up with different reduction sets and multiple indicators sharing the same weight. Therefore, this paper has further introduced the entropy weight method based on the weight solution determined by rough sets and solved the attribute reduction sets of different layers by using the Rosetta software. Finally, this paper has further proved the rationality of this evaluation model for atmospheric environment sustainability by comparing the results with those of the entropy weight method alone and those of the rough set method alone. The results show that the sustainability level of the atmospheric environment in Northeast China provinces has first improved, and then worsened, with the atmospheric environment sustainability level reaching the highest level of 0.9275 in 2014, while dropping to the lowest level of 0.6027 in 2017. Therefore, future efforts should focus on reducing the pressure layer and expanding the response layer. Based on analysis of the above evaluation results, this paper has further offered recommendations and solutions for the improvement of atmospheric environment sustainability in the three provinces of Northeast China.

scholarly journals A Combination Prediction Model of Long-Term Ionospheric foF2 Based on Entropy Weight Method

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 442
Author(s):  
Hongmei Bai ◽  
Feng Feng ◽  
Jian Wang ◽  
Taosuo Wu
Keyword(s):  
Prediction Model ◽  
Navigation Systems ◽  
Entropy Weight ◽  
Individual Model ◽  
Calibration Period ◽  
Average Percentage ◽  
Percentage Improvement ◽  
Entropy Weight Method ◽  
Weight Method

It is critically meaningful to accurately predict the ionospheric F2 layer critical frequency (foF2), which greatly limits the efficiency of communications, radar, and navigation systems. This paper introduced the entropy weight method to develop the combination prediction model (CPM) for long-term foF2 at Darwin (12.4° S, 131.5° E) in Australia. The weight coefficient of each individual model in the CPM is determined by using the entropy weight method after completing the simulation of the individual model in the calibration period. We analyzed two sets of data to validate the method used in this study: One set is from 2000 and 2009, which are included in the calibration period (1998–2016), and the other set is outside the calibration cycle (from 1997 and 2017). To examine the performance, the root mean square error (RMSE) of the observed monthly median foF2 value, the proposed CPM, the Union Radio Scientifique Internationale (URSI), and the International Radio Consultative Committee (CCIR) are compared. The yearly RMSE average values calculated from CPM were less than those calculated from URSI and CCIR in 1997, 2000, 2009, and 2017. In 2000 and 2009, the average percentage improvement between CPM and URSI is 9.01%, and the average percentage improvement between CPM and CCIR is 13.04%. Beyond the calibration period, the average percentage improvement between CPM and URSI is 13.2%, and the average percentage improvement between CPM and CCIR is 12.6%. The prediction results demonstrated that the proposed CPM has higher precision of prediction and stability than that of the URSI and CCIR, both within the calibration period and outside the calibration period.

A fire risk assessment method based on the combination of quantified safety checklist and structure entropy weight for shopping malls

2021 ◽  
pp. 1748006X2098737
Author(s):  
Quanle Zou ◽  
Tiancheng Zhang ◽  
Wei Liu
Keyword(s):  
Evaluation Method ◽  
Research Result ◽  
Fire Risk ◽  
Living Standard ◽  
Shopping Malls ◽  
Entropy Weight ◽  
Essential Components ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Laws And Regulations

In recent years, various large- and medium-sized shopping malls have been essential components of each city with the speed-up of China’s urbanization process and the improvement of residents’ living standard. A method for evaluating fire risk in shopping malls based on quantified safety checklist and structure entropy weight method was proposed according to related literatures as well as laws and regulations by analyzing the characteristics of fires occurring in shopping malls in recent years. At first, the factors influencing the fire risk in shopping malls were determined by carrying out on-site survey and visiting related organizations to construct an evaluation index system for fires occurring in shopping malls; afterwards, a quantified safety checklist composed of four parts (i.e. safety grade, grade description, scoring criterion and index quantification) was established based on related laws and regulations; subsequently, index weights were determined by utilizing structure entropy weight method, thus putting forward a method for assessing fire risk in shopping malls based on quantified safety checklist and structure entropy weight method. Eventually, the applicability of the evaluation method was validated exampled by Wal-Mart. The research result provides a theoretical basis for further improvement of the theoretical system for fire risk evaluation in shopping malls, and also exerts practical and guidance significance on timeous and effective early warning as well as prevention and control of building fires.

Research on Degree Evaluation of Rural Waste Recycling of Heilongjiang Province Based on the Integrated Evaluation Method

2011 ◽  
Vol 347-353 ◽  
pp. 1735-1739
Author(s):  
Jie Shang ◽  
Yuan Yao
Keyword(s):  
Index System ◽  
Agricultural Waste ◽  
Waste Recycling ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Heilongjiang Province ◽  
Entropy Weight ◽  
Development Direction ◽  
Entropy Weight Method ◽  
Weight Method

This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.,This paper has analyzed the degree of agricultural waste recycling utilization, and problems existing in current rural calculated degree of waste recycling in Heilongjiang province, using AHP and entropy weight method integrated and construct the rural waste recycling system, and points out that the evaluation index system of agricultural waste recycling after the development direction.

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