Research on Water-Filled Source Identification Technology of Coal Seam Floor Based on Multiple Index Factors

According to the No. 13 Mine of Pingdingshan Coal Co. Ltd., the fault dimension of the study area is calculated based on fractal theory. The four impact factors such as water inflow, water pressure, water inrush coefficient, and fault fractal dimension of 21 water boreholes are used as evaluation indices, and a mathematical model for identifying the water-filled source of the coal seam floor is established by coupling an entropy weight method and fuzzy variable set theory. The model is used to identify the water-filled source of 7 boreholes, which provide a reliable reference for the identification of the water-filled source. According to the calculation result of the entropy weight method, the water volume per unit of the borehole and the groundwater pressure have a significant impact on the water source identification, which accounts for 89.93% of the weight value. In the fuzzy variable set model, when the distance parameter p is 1 and the optimization criterion parameter α is 2, the accuracy of the water sample identification of the water source category to be identified is 85.71%, which is at a high recognition level. The more typical the impact factors selected and the more samples, the accuracy of water-filled source identification is much higher.

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Urban Flood Vulnerability Assessment Using the Entropy Weight Method

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2020.20.6.389 ◽

2020 ◽

Vol 20 (6) ◽

pp. 389-397

Author(s):

Seonmi Lee ◽

Youngje Choi ◽

Jaeeung Yi

Keyword(s):

Adaptive Capacity ◽

Heavy Rainfall ◽

Flood Damage ◽

Impact Factors ◽

Entropy Weight ◽

Flood Vulnerability ◽

Local Characteristics ◽

Climate Exposure ◽

Entropy Weight Method ◽

Weight Method

Locally concentrated heavy rainfall has led to an increase in the occurrence of flood damage. This is especially so in the urban areas, which are relatively more vulnerable to flood damage due to the high population and property density. In Seoul, which has 25 administrative districts, heavy rainfall triggered flood-related damage in 2010, 2011, and 2018. However, the flood characteristics of each district were different due to difference in flood impact factors such as topography, weather, and disaster prevention measures. The flood vulnerability of each district should be assessed based on local characteristics to reduce flood damage. This study collected and calculated 15 characteristic data points that can explain the climate exposure, sensitivity, and adaptive capacity of each district using the entropy weight method. Thereafter, the flood vulnerability of each district was calculated based on climate exposure, sensitivity, and adaptive capacity, using the Euclidean method. The results showed that the northern and western areas in Seoul are highly vulnerable due to high climate exposure, sensitivity, and low adaptive capacity. In contrast, the other parts of Seoul had low vulnerability due to high sensitivity, low climate exposure, and high adaptive capacity. These results will contribute to the establishment of a flood damage reduction plan that reflects local characteristics.

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The influence of digital economy on the upgrading of industrial structure

E3S Web of Conferences ◽

10.1051/e3sconf/202127501047 ◽

2021 ◽

Vol 275 ◽

pp. 01047

Author(s):

Siyu Liu

Keyword(s):

Industrial Structure ◽

Empirical Test ◽

Digital Economy ◽

Practical Significance ◽

Entropy Weight ◽

High Quality ◽

Starting Point ◽

Entropy Weight Method ◽

Weight Method ◽

The Impact

Digital economy is an important starting point for China’s high-quality economic development, which may have an impact on the level of industrial structure. This paper calculates the development level of digital economy by entropy weight method, selects the relevant data of 31 provinces and cities in China from 2012 to 2019, and uses the method of empirical test to analyze the impact of the development of digital economy on the upgrading of China’s industrial structure. The result shows that the development of digital economy can promote the upgrading of China’s overall industrial structure, which is significant at the level of 1%. Further research shows that the development of digital economy has regional heterogeneity on the upgrading of industrial structure in the eastern, central and western regions of China. The research of this paper has important practical significance for the high-quality development of China’s economy.

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Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

Sustainability ◽

10.3390/su11174556 ◽

2019 ◽

Vol 11 (17) ◽

pp. 4556 ◽

Cited By ~ 5

Author(s):

Boyang Sun ◽

Xiaohua Yang ◽

Yipeng Zhang ◽

Xiaojuan Chen

Keyword(s):

Data Envelopment Analysis ◽

Water Use Efficiency ◽

Water Use ◽

Water Shortage ◽

Data Envelopment ◽

Entropy Weight ◽

Entropy Weight Method ◽

Weight Method ◽

Use Efficiency ◽

The Impact

China’s water shortage problem is becoming increasingly severe. Improving water use efficiency is crucial to alleviating China’s water crisis. This paper evaluates the water use efficiency of 31 provinces and municipalities in China by using the data envelopment analysis (DEA) method. When the usual DEA model has too many indexes selected, it will cause the majority of the decision making units (DMUs) efficiency values be one, which leads to invalid evaluation results. Therefore, by using the entropy weight method, a new synthetic set of indexes is constructed based on the original indexes. The new synthetic set of indexes retains the full information of the original indexes, and the goal of simplifying the number of indexes is achieved. Simultaneously, by empowering the original indexes, the evaluation using synthetic indexes can also avoid the impact of industrial structure and labor division on water use efficiency. The results show that in China’s northeastern grain producing areas, water use efficiency is higher due to the high level of agricultural modernization. The provinces in the middle reaches of the Yangtze River have the lowest water use efficiency due to water pollution and water waste. In general, China’s overall water use efficiency is low, and there is still much room for improvement.

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Effectiveness of Entropy Weight Method in Decision-Making

Mathematical Problems in Engineering ◽

10.1155/2020/3564835 ◽

2020 ◽

Vol 2020 ◽

pp. 1-5 ◽

Cited By ~ 5

Author(s):

Yuxin Zhu ◽

Dazuo Tian ◽

Feng Yan

Keyword(s):

Decision Making ◽

Water Source ◽

Entropy Weight ◽

Weighting Method ◽

Numerical Discrimination ◽

Differentiation Degree ◽

Entropy Weight Method ◽

Weight Method ◽

Degree Of Differentiation ◽

Index Weight

Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

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Information Content Measurement of ESG Factors via Entropy and Its Impact on Society and Security

Information ◽

10.3390/info12100391 ◽

2021 ◽

Vol 12 (10) ◽

pp. 391

Author(s):

Hossein Hassani ◽

Stephan Unger ◽

Mohammad Reza Entezarian

Keyword(s):

Information Content ◽

Information Gain ◽

Entropy Weight ◽

Noisy Information ◽

Entropy Information ◽

The Social ◽

Entropy Weight Method ◽

Weight Method ◽

The Difference ◽

The Impact

We conducted a singular and sectoral vulnerability assessment of ESG factors of Dow-30-listed companies by applying the entropy weight method and analyzing each ESG factor’s information contribution to the overall ESG disclosure score. By reducing information entropy information, weaknesses in the structure of a socio-technological system can be identified and improved. The relative information gain of each indicator improves proportionally to the reduction in entropy. The social pillar contains the most crucial information, followed by the environmental and governance pillars, relative to each other. The difference between the social and economic pillars was found to be statistically not significant, while the differences between the social pillar, respective to the economic and governance pillars were statistically significant. This suggests noisy information content of the governance pillar, indicating improvement potential in governance messaging. Moreover, we found that companies with lean and flexible governance structures are more likely to convey information content better. We also discuss the impact of ESG measures on society and security.

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Development of a Sustainability Assessment Algorithm and Its Validation Using Case Studies on Cryogenic Machining

Journal of Manufacturing and Materials Processing ◽

10.3390/jmmp4020042 ◽

2020 ◽

Vol 4 (2) ◽

pp. 42 ◽

Cited By ~ 2

Author(s):

Prathamesh Bhat ◽

Chetan Agrawal ◽

Navneet Khanna

Keyword(s):

Case Studies ◽

Sustainability Assessment ◽

Decision Makers ◽

Machining Processes ◽

Entropy Weight ◽

Proposed Model ◽

Order Preference ◽

Entropy Weight Method ◽

Weight Method ◽

The Impact

This work presents a comprehensive structure for evaluating the sustainability of machining processes. Industries can contribute towards developing a sustainable future by using algorithms that evaluate the sustainability of their processes. Inspired by the literature, the proposed model involves a set of metrics that are critical in evaluating the impact of a process on society, environment, and economy. The flexibility of this model allows decision-makers to use the available responses to identify the most favorable process. The entropy weight method was suggested for objectively calculating the weights of each indicator. A multi-criteria decision-making method i.e., Technique for Order Preference based on Similarity to Ideal Solution (TOPSIS), was used to rank processes in the decreasing order of their sustainability. The proposed algorithm was successfully validated with case studies from the published literature. A MATLAB code was also created so that industries may expeditiously apply this method to evaluate the sustainability of machining processes.

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An Evaluation Model for The Impact of Climate Change on Regional Instability

MATEC Web of Conferences ◽

10.1051/matecconf/201817504022 ◽

2018 ◽

Vol 175 ◽

pp. 04022

Author(s):

Jia-Yi Lie ◽

Hong-Yu Duan ◽

Dong Chen

Keyword(s):

Climate Change ◽

Evaluation Model ◽

Entropy Weight ◽

Analytic Hierarchy ◽

Climate Change Impact Assessment ◽

Entropy Weight Method ◽

Weight Method ◽

Change Impact ◽

The Impact ◽

Hierarchy Process

The complication that climate change brings about has been an important issue in recent decades. In this paper, we attempt to find the inner connection between climate change and regional instability, and finally build a novel evaluation model about it. By innovatively utilizing Analytic Hierarchy Process and Entropy Weight Method combined, our model can produce a reliable climate change impact assessment. Empirical results on states of different stability provide strong evidence that our model possesses high feasibility and accuracy in practical use.

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