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Through the analysis of the risk transmission mechanism of chemical substances in toys, this paper identifies risk sources, transmission carriers, key nodes, and risk recipients, and draws a risk transmission path diagram. Taking the risk factors in the supply chain system as the research subject, this paper constructs a risk index system for chemical substances' limit in toys, and calculates the probability of risk and the degree of influence by the fuzzy evaluation method. Based on the Bayesian network model, this paper analyzes the causality of risk transmission effects. Through the comprehensive use of fuzzy evaluation and Bayesian network methods, a relatively complete chemical substance risk transmission path assessment system has been established using China's Guangdong toy companies as the data store to provide a feasible basis for responding to the risk control measures of toxic and hazardous chemical substances in toys. [ABSTRACT FROM AUTHOR]

Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for normal weather. Therefore, this paper proposes a systematic method based on numerical wind field and extreme learning machine for typhoon wind speed prediction of wind farms. The proposed method mainly consists of three parts, IGA-YanMeng typhoon numerical simulation model, typhoon status prediction model, and wind speed simulation model based on an extreme learning machine. The IGA-YanMeng typhoon numerical simulation model can greatly enrich typhoon wind speed data according to historical typhoon parameters. The typhoon status prediction model can predict the status of typhoons studied in the next few hours. And wind speed simulation model simulates the average wind speed magnitude/direction at 10 m height of each turbine in the farm according to the predicted status. The end of this paper presents a case study on a wind farm located in Guangdong province that suffered from the super typhoon Mangkhut landed in 2018. The results verified the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Logistics and economic development complement each other. The comprehensive competitiveness of Guangdong provincial economy ranks first in China. Under the influence of COVID-19, the freight development of Guangdong Province has been affected, but there is still lack of quantitative research. It is significant to explore the trend of economic development through the freight development of Guangdong Province. Based on the grey theory model, this paper uses six freight indexes to research freight development of Guangdong Province. Under the assumption that COVID-19 did not happen, we predicted the development value of freight index of Guangdong Province from January to December in 2020 and studied the influence based on the comparison between the predicted value and actual value. The empirical study shows three impact characteristics: stage characteristics, structural characteristics, and entity transmission characteristics. COVID-19 has a negative impact on the development of total freight volume, highway freight volume, waterway freight volume, and air freight volume in Guangdong Province. The influence values were −23.001%, −29.344%, −11.296%, and −3.838%. But, the freight volumes of railway and pipeline were positively affected by 14.343% and 13.057%, respectively, due to their continuity and substitution to other transportation modes. To further explore the abate measures of COVID-19 impact on Guangdong's freight development, the grey correlation model is introduced to study the correlation factors of freight development of Guangdong Province. Through the research of the related factors, this paper puts forward some measures to promote the freight development of Guangdong Province in the postepidemic era. [ABSTRACT FROM AUTHOR]

With the rapid development of rail transit, the excavation of new foundation pits will inevitably approach or pass through existing structures. Therefore, choosing a reasonable support scheme can effectively control the deformation of the foundation pit and ensure the safety of existing structures. This paper investigates the excavation of a typical foundation pit in Guangdong that underpasses a viaduct as the research object. This study uses field monitoring and numerical simulations to analyze the deformation characteristics of the supporting structure and introduces grey relational analysis (GRA) to investigate the key factors that influence the maximum horizontal deflection of the retaining wall. The results indicate that all monitored values are substantially less than the warning value specified in the code. Moreover, the horizontal deflection of the retaining wall and the horizontal displacement of the top of the wall at the measuring points near the existing bridge piles are smaller than at other measuring points. This support system has a high safety factor and a large space for optimization. The main factors affecting the maximum horizontal deflection of the retaining wall are as follows: second strut horizontal spacing > first strut horizontal spacing > layered excavation thickness > retaining wall thickness > retaining wall stiffness. The results of this study will provide technical guidance for the design of similar projects and optimization of their construction. [ABSTRACT FROM AUTHOR]

Objective. To carry out the research on the vulnerability evaluation and influencing factors of the tourism economic system is the objective requirement of formulating the scientific development strategy of the tourism economy and improving the quality of regional tourism development. Methods. Based on the vulnerability analysis of tourism economic system based on BP neural network (BPNN), this paper takes the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the research object and selects 14 index data. The mean and standard deviation of the calculated weight values are used to formulate evaluation criteria for the tourism system. Results. The BP neural network (BPNN) model was used to predict the distribution law of vulnerability data within the standard range of the Greater Bay Area after 2020, obtained the spatial distribution law of vulnerability in the geographic structure distribution of the Greater Bay Area, and determined the vulnerability analysis framework and evaluation method. Conclusion. The cities in the Greater Bay Area should first pay attention to the industrial structure; increase financial investment; enhance the attractiveness of tourist destinations, in-depth development of tourism resources, and rational design of tourism products; help reduce the vulnerability of the tourism economic system; and improve regional self-recovery capabilities. [ABSTRACT FROM AUTHOR]

Environmental problems have become a major factor affecting the world's economic development. In order to reduce environmental pollution and improve environmental quality. This paper takes Guangdong Province as the research object, adopts the basic principles of human capital method and medical cost usage environmental pollution loss cost, incorporates environmental factors into the national economic accounting system, establishes the green GDP cost accounting method, and develops the environmental pollution economic loss accounting index; it adopts the environmental pollution economic loss accounting method, counts the number of affected objects within the scope of environmental pollution, so as to establish a comprehensive environmental economic accounting system, incorporating environmental factors into the economic system; the economic losses calculated in accordance with the established environmental pollution accounting procedures, converting tangible losses into monetary losses and counting the environmental pollution costs caused by the economy of Guangdong Province, analyzing the root causes of the deficiencies and problems in environmental damage cost control in Guangdong Province, and proposing methods to effectively control the costs of air, water, solid waste, and polluted environment. The results of the study provide a new direction and basis for future industrial pollution control in Guangdong Province and take into account both social and economic benefits. [ABSTRACT FROM AUTHOR]

Public subsidies for offshore wind power will be eliminated in 2022. At present, offshore wind power still depends on subsidies. In this new situation, it is necessary to study the influence on the stakeholders and how the offshore wind power industry achieves healthy and sustainable development. Firstly, this paper qualitatively analyzes the impact of the cancellation of state subsidies on offshore wind turbine manufacturers and developers and finds that if there is no subsidy to relay offshore wind power, the development of offshore wind power will stagnate, and the wind turbine manufacturers will face great challenges. Then, by constructing the subsidy demand calculation model and the transmission and distribution price cross subsidy calculation model according to China's electricity price-related policies, the results show that the local subsidy is basically feasible to continue the national subsidy, and the burden is decreasing year by year, so the relay subsidy should be continued. Based on the cloud model, an evaluation model for the development of offshore wind power benefits from the cancellation of national subsidies is constructed to quantify the impact of the cancellation of overseas subsidies on local governments and power grid enterprises. According to the example analysis, under the background of the cancellation of national subsidies, Guangdong has the best development of offshore wind power benefits, which verifies the feasibility of the proposed model. [ABSTRACT FROM AUTHOR]