gray correlation
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2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chongyu Wang

The environmental protection attribute and energy-saving level of green buildings cannot be described by the traditional evaluation model. In order to solve the above problems, a new ecological energy-saving effect evaluation algorithm of green buildings based on gray correlation degree is designed. Based on the framework of building energy-saving index system, the environmental protection evaluation standards are divided and the results are used to screen the energy-saving indexes, so as to complete the establishment of green building ecological energy-saving index system and standards. Then, the evaluation set is established, and the evaluation scale of each layer of indicators is accurately located according to the weight value of each index. On this basis, the membership matrix is constructed. By calculating the index weight and determining the fuzzy synthesis operator, the rating process of the algorithm is improved and the analysis of the evaluation algorithm of environmental protection and energy conservation indicators of green building materials based on gray correlation degree is realized. The experimental results show that the designed algorithm has good stability of the fitting curve, can save energy, and has low cost.


2021 ◽  
Author(s):  
Chun Chen ◽  
Yue Sun

Based on the concept of green development, this paper constructs the comprehensive evaluation system to measure the development level of digital economy in Hubei Province and uses the entropy method to calculate the development level with the relevant data during 2013-2019 years, analyzing the factors affecting the development of the digital economy in Hubei Province. In addition, this paper uses the gray correlation method to explore the relationship between influencing factors. The results show that the popularization level of digital technology and R&D innovation are the main engines to promote the development of digital economy in Hubei Province. The completed infrastructural facility can positively stimulate the application of digital technology and promote the digital development of enterprises. Therefore, Hubei Province should vigorously promote industrial integration, improve innovation ability, expand application scenarios and optimize digital governance to improve the development level of digital economy, so as to realize the green development of Hubei Province.


Author(s):  
Sipei Pan ◽  
Jiale Liang ◽  
Wanxu Chen ◽  
Jiangfeng Li ◽  
Ziqi Liu

A sound ecosystem is the prerequisite for the sustainable development of human society, and the karst ecosystem is a key component of the global ecosystem, which is essential to human welfare and livelihood. However, there remains a gap in the literature on the changing trend and driving factors of ecosystem services value (ESV) in karst areas. In this study, Guizhou Province, a representative region of karst mountainous areas, was taken as a case to bridge the gap. ESV in the karst areas was predicted, based on the land use change data in 2009–2018, and the driving mechanisms were explored through the gray correlation analysis method. Results show that a total loss of CNY 21.47 billion ESV from 2009 to 2018 is due to the conversion of a total of 22.566% of the land in Guizhou, with forest land as the main cause of ESV change. By 2025 and 2030, the areas of garden land, water area, and construction land in Guizhou Province will continue to increase, whereas the areas of cultivated land, forest land, and garden land will decline. The total ESV shows a downward trend and will decrease to CNY 218.71 billion by 2030. Gray correlation analysis results illuminate that the total population and tertiary industry proportion are the uppermost, among all the driving factors that affect ESV change. The findings in this study have important implications for optimizing and adjusting the land use structure ecological protection and will enrich the literature on ESV in ecologically fragile areas.


2021 ◽  
Vol 13 (22) ◽  
pp. 12923
Author(s):  
Wei Jiang ◽  
Yun Li ◽  
Jiankai Zhou ◽  
Zhishun Huang ◽  
Zonghao Wu

Compared with other types of transportation, hazardous chemical transportation is more dangerous and more likely to cause accidents, such as combustion and explosion. To better study the advantages of different accident analysis models and realize the sustainable development of the accident analysis, this paper compares the 24Model and the cognitive reliability and error analysis method in their analyses of causes of hazardous chemical transportation accidents. Regarding their analyses of the causes of hazardous chemical transportation accidents, the causal factors of hazardous chemical transportation accidents are obtained. Then the analysis results of the two models are compared on three aspects: the object of accident influence, the module of accident analysis, and the number of accident causes. Gray correlation analysis and regression analysis are used to quantitatively compare and verify the focus of the two models on the cause of the accident. The results show that the 24Model emphasizes the safety culture of the enterprise, the cognitive reliability and error analysis method emphasizes the technology of the enterprise, and the two accident analysis models provide different emphases on preventing accidents to better achieve the goal of sustainable development.


2021 ◽  
Vol 2083 (3) ◽  
pp. 032055
Author(s):  
Congli Wang ◽  
Xiong Li

Abstract Most of the image scrambling degree evaluation algorithms rely on the statistical features of the original image, which cannot achieve blind evaluation. Based on the uniform distribution model of the statistical characteristics of ideal scrambled images, a blind evaluation algorithm of image scrambling degree combining space and frequency domain is proposed in this paper. In the space domain, the uniform distribution characteristics of the gray histogram of the ideal scrambled image are used, and the uniform distribution characteristics of the Discrete Fourier Transform (DFT) spectrogram in the frequency domain are combined with the gray correlation analysis theory. The two are weighted to realize the space and frequency domain evaluation of the scrambled image performance. The experimental results indicate that the evaluation algorithm in this paper can consider the performance evaluation of both pixel value and pixel position dislocation, avoiding the disadvantage of ineffective spatial domain evaluation when only the pixel position scrambling is performed. It has very sensitive to the histogram distribution and frequency domain features of encrypted images, and has good agreement with Human Visual System (HVS). The original image is completely independent, and it enables blind evaluation objectively.


Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5523
Author(s):  
Jingsheng Pan ◽  
Hua Zhao ◽  
Yong Wang ◽  
Gang Liu

The influence of sand accumulation on the skid resistance of asphalt pavement was studied. Many scholars have researched the anti-skid performance of conventional asphalt pavements. However, there is a lack of research on the anti-skid performance of desert roads under the condition of sand accumulation. In this study, AC-13 and AC-16 asphalt mixtures were used. The British Pendulum Number (BPN) under different sand accumulations was measured with a pendulum friction coefficient meter, and the Ames engineering texture scanner was used to obtain different sand accumulations. The texture index of asphalt mixture was used to study the macro and micro texture of asphalt pavement under different amounts of sand accumulation, and the degree of influence of different particle sizes on BPN was obtained through gray correlation analysis. The test results show that the presence of aeolian sand has a significant impact on the macro and micro texture of the asphalt pavement and will cause the anti-skid performance to decrease. Moreover, there is an apparent positive linear correlation between the road surface texture index and BPN. The research results may provide reference and reference for the design and maintenance of desert highways.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wei Dong ◽  
Jia Zeng ◽  
Qin Wang ◽  
Xin Jiang ◽  
Ting Huang

Abstract Background Siraitia grosvenorii (binomial name Siraitia grosvenorii (Swingle) C. Jeffrey ex Lu et Z. Y. Zhang), also called Arhat Fruit or Monk’s Fruit, is a dried ripe fruit belonging to the Cucurbitaceae Family. S. grosvenorii has a long history of being used for constipation treatment in folk medicine. However, there are few studies where the laxative effect, related mechanisms, and active constituents of S. grosvenorii were investigated. This research explores the relationship between the common components and the laxative effect of aqueous extracts of S. grosvenorii from different habitats in China. Methods The fingerprints of S. grosvenorii aqueous extracts from different habitats were established by HPLC. The constipation mice model was used to investigate the laxative effect of S. grosvenorii aqueous extracts. The motilin (MTL) level in mice serum, and the water content of the large and small intestines in mice were determined. The profile-effect relationship of S. grosvenorii aqueous extracts was preliminarily clarified using gray correlation analysis. Results Nine common peaks were identified from the fingerprint of aqueous extracts of S. grosvenorii. The aqueous extracts obviously shortened the incubation period of defecation, and significantly increased the number of defecations, and the wet and dry weight of defecation in constipated mice. The profile-effect relationship indicated that seven common peaks were highly correlated with the effect of the incubation period of defecation, the number of defecations, and the wet and dry weight of defecation in mice. Conclusion This work provides a promising method for the fingerprint establishment, pharmacodynamic evaluation, and quality control of S. grosvenorii on the basis of its profile-effect relationship.


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