scholarly journals Analysis of Early Warning Spatial and Temporal Differences of Tourism Carrying Capacity in China’s Island Cities

2020 ◽  
Vol 12 (4) ◽  
pp. 1328 ◽  
Author(s):  
Fang Ye ◽  
Jaepil Park ◽  
Fen Wang ◽  
Xihua Hu
Keyword(s):  
Early Warning ◽  
Carrying Capacity ◽  
State Space Model ◽  
Back Propagation ◽  
Development Trend ◽  
Indicator System ◽  
Total System ◽  
Temporal Differences ◽  
Warning Interval ◽  
The Government

Tourism is the leading industry of island cities and the tourism carrying capacity is of great significance to the sustainable development of cities. This paper adopts the state-space model to construct an early warning indicator system for tourism carrying capacity from three aspects: nature, economy, and society, explores the early warning status, and spatial and temporal differences of tourism carrying capacity in Chinese island cities, and makes use of the BP(Back Propagation) neural network model to predict the development trend of early warnings. The results show that (1) from 2012 to 2018, the early warning status of China’s island cities’ tourism carrying capacity is generally on the rise, the natural carrying capacity system’s early warning situation has deteriorated, which is in a state of severe warning interval. The economic carrying capacity and social carrying capacity are on the rise, and the warning degree is from the super warning interval to the severe warning interval and then to the moderate warning degree. The forecast of the overall tourism carrying capacity early warning index from 2019 to 2021 presents an upward trend and is in the moderate warning interval. (2) The tourism carrying capacity early warning in China’s island cities shows a large spatial and temporal difference and the early warning values of each island city are different. The early warning value of Putuo tourism carrying capacity always ranks first, and Changdao has the worst performance. (3) In accordance with the contribution status of the subsystem to the total system, the Chinese island cities show regional differences in the northern, central, and southern area, showing two forms of pressure cities and pressure-carrying cities. The government can adopt different policies and measures in accordance with different characteristics of human environmental activities.

scholarly journals Evaluation of China’s Circular Agriculture Performance and Analysis of the Driving Factors

2021 ◽  
Vol 13 (4) ◽  
pp. 1643
Author(s):  
Biao Li ◽  
Yunting Feng ◽  
Xiqiang Xia ◽  
Mengjie Feng
Keyword(s):  
Rapid Development ◽  
Arable Land ◽  
Indicator System ◽  
Resource Scarcity ◽  
Entropy Method ◽  
Agricultural Industry ◽  
Evaluation Indicator ◽  
Evaluation Indicator System ◽  
Per Capita ◽  
The Government

Along with industry upgrading and urbanization, the agricultural industry in China has been experiencing a stage of rapid development, on the bright side. On the other side, ecological environment deterioration and resource scarcity have become prevalent. Called by the current situation, circular agriculture arises as a direction for the industry to achieve sustainable development. This study develops an evaluation indicator system for circular agriculture using an entropy method, and evaluates factors that could drive the Chinese agricultural industry to achieve better performance. We employ the method using provincial data collected from the province of Henan, in which around 10% of the total grain in China is produced. It was found that agricultural technology and water resources per capita are positively related to circular performance in agriculture. In contrast, urbanization and arable land per capita are negatively related to circular performance. This article provides support to the government in policy-making related to the improvement of circular agricultural performance.

scholarly journals The Sustainable Development of Financial Topic Detection and Trend Prediction by Data Mining

2021 ◽  
Vol 13 (14) ◽  
pp. 7585
Author(s):  
Yunmei Liu ◽  
Shuai Zhang ◽  
Min Chen ◽  
Yenchun Wu ◽  
Zhengxian Chen
Keyword(s):  
Data Mining ◽  
Supply Chain ◽  
Financial Institutions ◽  
Clustering Algorithm ◽  
Development Trend ◽  
Research Field ◽  
Trend Prediction ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
The Government

Blockchain technology is the most cutting-edge technology in the field of financial technology, which has attracted extensive attention from governments, financial institutions and investors of various countries. Blockchain and finance, as an interdisciplinary, cross-technology and cross-field topic, has certain limitations in both theory and application. Based on the bibliometrics data of Web of Science, this paper conducts data mining on 759 papers related to blockchain technology in the financial field by means of co-word analysis, bi-clustering algorithm and strategic coordinate analysis, so as to explore hot topics in this field and predict the future development trend. The experimental results found ten research topics in the field of blockchain combined with finance, including blockchain crowdfunding, Fintech, encryption currency, consensus mechanism, the Internet of Things, digital financial, medical insurance, supply chain finance, intelligent contract and financial innovation. Among them, blockchain crowdfunding, Fintech, encryption currency and supply chain finance are the key research directions in this research field. Finally, this paper also analyzes the opportunities and risks of blockchain development in the financial field and puts forward targeted suggestions for the government and financial institutions.

scholarly journals Safety Warning Model of Coal Face Based on FCM Fuzzy Clustering and GA-BP Neural Network

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1082
Author(s):  
Fanqiang Meng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Early Warning ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Coal Face ◽  
Early Warning Model ◽  
Working Face ◽  
The Neural Network ◽  
Warning Model

Risk and security are two symmetric descriptions of the uncertainty of the same system. If the risk early warning is carried out in time, the security capability of the system can be improved. A safety early warning model based on fuzzy c-means clustering (FCM) and back-propagation neural network was established, and a genetic algorithm was introduced to optimize the connection weight and other properties of the neural network, so as to construct the safety early warning system of coal mining face. The system was applied in a coal face in Shandong, China, with 46 groups of data as samples. Firstly, the original data were clustered by FCM, the input space was fuzzy divided, and the samples were clustered into three categories. Then, the clustered data was used as the input of the neural network for training and prediction. The back-propagation neural network and genetic algorithm optimization neural network were trained and verified many times. The results show that the early warning model can realize the prediction and early warning of the safety condition of the working face, and the performance of the neural network model optimized by genetic algorithm is better than the traditional back-propagation artificial neural network model, with higher prediction accuracy and convergence speed. The established early warning model and method can provide reference and basis for the prediction, early warning and risk management of coal mine production safety, so as to discover the hidden danger of working face accident as soon as possible, eliminate the hidden danger in time and reduce the accident probability to the maximum extent.

scholarly journals Revealing Development Trends and Key 5G Photonic Technologies Using Patent Analysis

2019 ◽  
Vol 9 (12) ◽  
pp. 2525 ◽  
Author(s):  
Shu-Hao Chang
Keyword(s):  
Semiconductor Industry ◽  
Development Trend ◽  
Market Development ◽  
Development Research ◽  
Optical Elements ◽  
Technological Field ◽  
Key Technologies ◽  
The Government ◽  
Information Technology Companies ◽  
The Development Trend

In recent years, 5G photonic technology has gradually gained increased attention from scholars. However, studies on 5G photonic technology have mostly focused on technological discussions or market development research, but have failed to identify the relevant key technologies from a comprehensive perspective. In particular, 5G photonic technology is an interdisciplinary technology that could create considerable potential business opportunities in the future, therefore, identifying related key technologies is crucial. Accordingly, the patents of 5G photonic technologies were used as the basis for analysis in this study, and a patent technology network for such technologies was constructed using network analysis. The results showed that the key technologies of 5G photonic technology are mainly related to optics, nanostructures, semiconductors, and material analysis, indicating an interdisciplinary feature instead of focusing only on one specific technological field. Additionally, the relevant technologies that have seen active development in recent years are mainly related to optical elements and semiconductor devices. Finally, a patentee analysis demonstrated that information technology companies were the key players in the development of 5G photonic technologies, and the semiconductor industry will have a crucial role in the development of such technologies. In this study, a patent technology network model was constructed to explore the development trend of 5G photonic technologies, thereby providing a reference for the government to promote these emerging technologies.

scholarly journals The Research of Coal and Gas Outburst Warning Based on Logistic Regression and Geographic Information System

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bo You ◽  
Bo Li ◽  
Shi Liang Shi ◽  
He Qing Liu ◽  
Yi Lu ◽  
...  
Keyword(s):  
Information System ◽  
Logistic Regression ◽  
Geographic Information System ◽  
Early Warning ◽  
Warning System ◽  
Indicator System ◽  
Geographic Information ◽  
Coal And Gas Outburst ◽  
Gas Outburst ◽  
Early Warning Indicator

Coal and gas outburst is one of the major disasters in the safety production of coal mine. According to the mechanism of coal and gas outburst, based on the comprehensive analysis of various influencing factors of coal and gas outburst, with the principles of selected early warning indicator, the basic information database of coal and gas outburst warning is constructed, and the information data query function is realized. The mathematical model of coal and gas outburst warning is established by the logistic regression analysis based on the gas concentration, the gas desorption index of drill cuttings, and the initial velocity of gas emission from the borehole. The multivariate information coupled warning was conducted according to the selected early warning indicator system, and the early warning level was divided with the result of early warning. The design and research of the coal and gas outburst warning system are carried out based on the geographic information system (GIS). The coal and gas outburst warning system was verified by taking the Tunliu mine of Lu’an Group as an example. The establishment of the early warning system is a new technical way to the early warning management of coal and gas outburst and can provide a guarantee for coal and gas outburst prevention.

scholarly journals Evaluation of Airport Environmental Carrying Capacity: A Case Study in Guangzhou Baiyun International Airport, China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lili Wan ◽  
Qiuping Peng ◽  
Tianci Zhang ◽  
Zhan Wang ◽  
Yong Tian
Keyword(s):  
Carrying Capacity ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Projection Pursuit ◽  
Indicator System ◽  
Development Mode ◽  
The Sustainable Development ◽  
International Airport ◽  
Environmental Carrying Capacity

In order to clarify the comprehensive operational capabilities of the airport and better plan the sustainable development mode of the airport, this paper studies the evaluation method of airport environmental carrying capacity. First, this paper proposes the concept of airport environmental carrying capacity by taking into account the complex characteristics of airports affected by multiple factors and then selects 16 representative evaluation indicators to construct an indicator system based on the Driving Force-Pressure-State-Response (DPSR) framework. Finally, the accelerated genetic algorithm-projection pursuit model is established to model a comprehensive evaluation index, which is used to calculate the airport environmental carrying capacity (AECC). The results of the case study show that the AECC of Guangzhou Baiyun International Airport (CAN) decreased year by year from 2008 to 2017, which is in line with the coordinated development level of CAN. By analysing the changing mechanism of AECC and indicators, we get 6 key influencing indicators that led to the continuous decline of AECC and put forward some political suggestions to improve the AECC.

scholarly journals Development Trend of Smart Home Industry A case study of Haier Smart Home

2021 ◽  
Vol 14 ◽  
pp. 194-207
Author(s):  
Yiru Pan ◽  
Yuehan Wu ◽  
Yuanwu Xin
Keyword(s):  
Smart Home ◽  
Product Life Cycle ◽  
Good Condition ◽  
Development Trend ◽  
Sales Channels ◽  
Product Logic ◽  
Growth Space ◽  
Asset Turnover ◽  
Home Appliance ◽  
The Government

In recent years Smart Home appliance is a research hotspot in the home appliance industry. It is the product of a series of high-end technologies such as the Internet of Things, 5G, and AI, and is in the growth stage of the product life cycle. In this paper, the PESTAL analysis method and Porter's Five Forces model are used to analyze the environment and competition in the Chinese smart home industry. It is found that the generation of Smart Home conforms to the upgrading of social demand and economic development, so it is supported by the government. However the industry now lacks a unified technology connector, resulting in the fragmentation and isolation of current products from different producers. This paper also takes Haier Smart Home as an example, focusing on its analysis of product logic chain and of financial status. Through the establishment of seven brands, Haier Smart Home has created a perfect product system, which can meet the multi-level demand of middle and high-end, and ranks high in sales. Contrast to its competitors, Haier Smart Home's complex ownership structure and overlapping sales channels do harm to the efficiency of its operation, which eventually result in a low-profit margin, but its sales are high, and asset turnover also maintains at a good level, so the company overall operation is in good condition, and its future growth space is large.

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