Research and Optimization of the Coupling and Coordination of Environmental Regulation, Technological Innovation, and Green Development

Environmental regulation and technological innovation play important strategic roles in green growth, and the three systems interact and influence each other. Herein, we used a comprehensive development level evaluation model for calculating the environmental regulation and technological innovation indices for 17 cities in Shandong Province. We used the slack-based measure-data envelopment analysis (SBM-DEA) model to measure green development efficiency. The coupling coordination degree model was used to determine the coordination of environmental regulation, technological innovation, and green development; we divided the cities into three systems: green economy lagging, environmental regulation lagging, and technological innovation lagging. We used grey correlation analysis to explore the factors affecting system development. Eastern coastal cities were better developed in the three systems and the degree of coupling and coordination, like Qingdao and Weihai, and the observed level of technological innovation development, a critical factor in the coordinated development of cities, was lowest in Shandong Province. The grey correlation analysis illustrated that the level of economic development and the level of foreign economic development impacts cities labeled green economy lagging; the impact of pollutant emissions is greater than pollution control expenditure in environmental regulation lagging cities; and the government’s attention and the cultivation and attraction of talent are foundational for technological innovation in lagging cities. Considering these factors, we make recommendations for the optimal development of cities and coordinated development of regions.

Effect of electrolysis parameters on corrosion resistance of extra-low carbon high silicon iron-based alloy

Purpose High silicon iron-based alloys possess excellent corrosion resistance in certain specific media, but the effects of electrolysis parameters on corrosion resistance remain unknown. This study aims to guide the development and application of an extra-low carbon high silicon iron-based alloy (ECHSIA) in electrode plates. Design/methodology/approach The corrosion resistance of ECHSIA and a conventional high-silicon cast iron (CHSCI) was analyzed through experimental characterizations. The morphology was observed by scanning electron microscopy. The influence of electrolysis parameters on the corrosion resistance of ECHSIA was investigated through corrosion experiments. The relationship between the electrolysis parameters and the corrosion resistance of ECHSIA was statistically investigated using the grey correlation analysis method. Findings The corrosion resistance of the ECHSIA is better than that of the CHSCI. The corrosion rate showed an increasing tendency with the increase in the nitric acid concentration (CHNO3), electrolyte temperature and current density. The grey correlation analysis results showed that the CHNO3 was the main factor affecting the corrosion rate of the ECHSIA. Originality/value An ECHSIA with a single ferrite microstructure was prepared. This study provides a guideline for the future development and application of ECHSIAs as electrode plates.

Identification of low-voltage connection relation in distribution platform based on similarity of voltage curve and grey correlation degree of entropy weight

The correct low-voltage connection relationship in distribution area is of great significance to the safe operation and efficient management of power grid. As there are many reconstruction projects in the low-voltage platform area, the assets change frequently, and the interconnection perception ability of the low-voltage platform area is weak, which brings great difficulties to the identification of the user connection relationship. Traditional identification methods are heavy and inefficient. This paper proposes a method based on trend similarity and distance measure to identify low-voltage connection relation in distribution platform area. Firstly, Pearson correlation coefficient and discrete Fréchet distance are calculated to measure the trend similarity of voltage curve, and abnormal users are found out. GIS is used to search for adjacent stations, and finally, the correct station area of users is determined by analyzing the entropy weight grey correlation degree. The applicability and correctness of the proposed algorithm are verified by the application results of an example.

Detection of Body Behavior Characteristics in Sports Training Based on Grey Relational Model

In order to deal with the problems of low detection accuracy and efficiency existing in traditional detection methods of body behavior characteristics in sports training, this paper proposes a new detection method of body behavior characteristics in sports training based on the grey correlation model. According to this method, the foreground binary image is obtained by the interframe difference method, and the action information and contour information are extracted, firstly. And then, the behavior feature descriptor is obtained. After the description of body behavior characteristics in sports training is completed, the grey correlation coefficient is calculated, and the complete observation equation of time delay estimation of image grey value under complex sports training background is established to complete the detection of body behavior characteristics. The experimental results show that, compared with the traditional methods, the detection accuracy and efficiency of the text method can always maintain a high level, indicating that the practical application performance of this method is strong. In fact, the grey analysis does not attempt to find the best solution but does provide techniques for determining a good solution.

Grey Correlation Analysis of Haze Impact Factor PM2.5

In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to study the correlation between haze weather and local climate. First, we select Beijing, China and its surrounding areas (East longitude 115°20′11″–117°40′35″, North latitude 39°21′11″–41°7′51″) as the study area. We collected data from meteorological stations in Beijing and Xianghe from March 2014 to February 2015, and analyzed the meteorological parameters through correlation analysis and a grey correlation model. We study the correlation between the six influencing factors of temperature, dew point, humidity, wind speed, air pressure and visibility and PM2.5, so as to analyze the correlation between haze weather and local climate more comprehensively. The results show that the influence of each index on PM2.5 in descending order is air pressure, wind speed, humidity, dew point, temperature and visibility. The qualitative analysis results confirm each other. Among them, air pressure (correlation 0.771) has the greatest impact on haze weather, and visibility (correlation 0.511) is the weakest.

Evaluation of Factors Influencing Energy Consumption in Water Injection System Based on Entropy Weight-Grey Correlation Method

In order to determine the importance of influencing factors of energy consumption in oilfield water injection systems, the distribution of energy loss in the water injection system was analyzed, the factors affecting the energy consumption of the water injection system were determined, and an evaluation index system for the energy consumption of the water injection system was established. This indicator system covers all links and all energy loss nodes of the energy loss of the water injection system, thereby an evaluation model for influencing factors of energy consumption in water injection system based on entropy weight - grey correlation method was built. Use the entropy weight method to get the ranking of the importance of energy consumption indicators; use the gray correlation method to determine the correlation between each water injection system and energy consumption factors. The application results show that the entropy weight-grey correlation method proposed in this paper can effectively obtain the importance of the energy consumption factors of the oilfield water injection system, and provide scientific guidance for the daily management and targeted optimization of the water injection system.