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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]

Under the background of "one belt, one road initiative" and the "Outline Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area," Guangdong, Hong Kong, and Macao port group development is facing new opportunities. The port group has a large throughput, covering the hinterland with dense population and high economic density, excellent transportation infrastructure, and broad consumption market. However, the port group internal competition is fierce, and the development level is different in space. Based on this, this paper uses the HHI index and spatial economics as research method and aims to study the spatial evolution characteristics and influencing factors of Guangdong-Hong Kong-Macao port group. Firstly, the HHI index is used to describe the aggregation status. Secondly, the development level index according to port throughput and container throughput is constructed. The spatial development and evolution process of the port group of Guangdong, Hong Kong, and Macao is analyzed by combining with spatial econometrics and economic geography. In summary, the influencing factor "diamond model" is constructed and took empirical research to verify its rationality and scientificity. The empirical results show a strong spatial correlation between the development of the Guangdong, Hong Kong, and Macao port group. The government intervention and the development of port industry have a negative correlation, and this impact will be weakened over time. There is a negative relationship between the level of marketization and the development of the port industry. There is a multiple and complex relationship between the port auxiliary industry and the development of the port industry, and it shows the short-term influence is smaller than the long-term impact. The level of port transportation infrastructure, the port industry competition, and the economic openness have significant and positive effects on the development of the port group. [ABSTRACT FROM AUTHOR]

The construction of the Guangdong-Hong Kong-Macao Greater Bay Area requires the establishment of a comprehensive port cooperation mechanism. Coordination is key to port integration. This paper establishes a multi-group Lotka-Volterra model based on the theory of competition and cooperation to study the evolution of the relationships among Hong Kong Port, Shenzhen Port, and Guangzhou Port. The results show that the three major ports have predator-prey roles and form a symbiotic competition and cooperation ecological pattern. The extended Hotelling model is established to study the central ports' spatial differences; the results show that whether it is the central port cooperation body or the entire central port group, the gains from Shenzhen Port-Guangzhou Port cooperation are greater than between either and Hong Kong Port for Guangdong-Hong Kong-Macao Greater Bay Area's container business. The biggest competitor to Hong Kong Port in the container business is Guangzhou Port. Hong Kong Port will gain more from cooperation with Shenzhen Port and should strengthen such cooperation. The study provides quantitative support and reference for positioning the strategic development of the high-end shipping business in Hong Kong Port, the pilot free-trade port in Shenzhen Port, and the exploration of the Shenzhen-Hong Kong composite port, Guangzhou Port's comprehensive shipping hub. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new slash distribution via the power normal distribution and uniform distribution. This new distribution, called the slash power normal distribution, models more appropriately the skewness and kurtosis of data than the power normal distribution. Moreover, the probability density function and the cumulative distribution function of the slash power normal distribution are derived and the density function curves with different parameters are given. We also study the basic properties of the moments, derive the maximum likelihood estimation of the parameters, and substantiate our arguments with numerical simulations. Finally, we model hourly measurements of sulphur dioxide concentrations of a station in Hong Kong by the slash power normal distribution, power normal distribution, and skew normal distribution and use the K-S test to evaluate the model fittings. The result demonstrates that the slash power normal distribution gives a better fit to the data. [ABSTRACT FROM AUTHOR]

Let B = B t 1 , ... , B t d t ≥ 0 be a d -dimensional bifractional Brownian motion and R t = B t 1 2 + ⋯ + B t d 2 be the bifractional Bessel process with the index 2 HK ≥ 1 . The Itô formula for the bifractional Brownian motion leads to the equation R t = ∑ i = 1 d ∫ 0 t B s i / R s d B s i + HK d − 1 ∫ 0 t s 2 HK − 1 / R s d s . In the Brownian motion case K = 1 and H = 1 / 2 , X t ≔ ∑ i = 1 d ∫ 0 t B s i / R s d B s i , d ≥ 1 is a Brownian motion by Lévy's characterization theorem. In this paper, we prove that process X t is not a bifractional Brownian motion unless K = 1 and H = 1 / 2 . We also study some other properties and their application of this stochastic process. [ABSTRACT FROM AUTHOR]

This paper reviews the progress of the multiple population mortality model and the defects in parameter estimation and proposes an effective method to improve the performance of the mortality model. We set up a multiple population group, using the data of mainland China, Hong Kong (China), and Japan, to test fitting performance and forecasting performance. Using the TSWLS and TSSVD methods in a multiple population stochastic mortality model has advantages in fitting performance and robustness. In addition, the forecasting value of mortality ratio between any two populations can converge to a fixed constant in a certain time period which obeys the regular of human biological characteristics. [ABSTRACT FROM AUTHOR]

This paper selects improved maximum likelihood method to conduct parameter estimation of Heston model, and results show that the share option pricing performance of Hang Seng Index is better and pricing error of at-the-money options is the smallest. By comparing parameter estimation of samples in different intervals, it has been found that parameter estimated results of two-year market data are obviously inferior to estimated effect of one-year data. [ABSTRACT FROM AUTHOR]

The port groups of the Guangdong-Hong Kong-Macao Greater Bay Area faces a new competitive and cooperative game structure concerning global competition, making it is necessary to build a comprehensive port coordination and development mechanism. In this study, we apply the logistics model to conduct parameter estimation and evolution trend analysis on the development of the port group and highlight that the current container throughput of the Guangdong-Hong Kong-Macao Greater Bay Area port group will reach the maximum and the new impetus is needed to push it into the next round of development and evolution. Combined with the theory of ecological population, the Lotka–Volterra model of multiple groups is introduced to study competition and cooperation game, explore their interaction, and provide quantitative support for the formation of different central port groups in the Guangdong-Hong Kong-Macao Greater Bay Area. The study provides references for strengthening the construction of complementary resources and coordinated mechanism within the port group, realizing the differential development between ports in the Guangdong-Hong Kong-Macao Greater Bay Area. [ABSTRACT FROM AUTHOR]

The current educational development in the Guangdong-Hong Kong-Macao Greater Bay Area is not enough to support the construction of a world-class bay area, so the education reform and innovation in the Greater Bay Area face many challenges. This study systematically sorts out the challenges faced by education in the Guangdong-Hong Kong-Macao Greater Bay Area, starting from the interpretation of the talent training standards in the new era, and proposes that the education innovation in the Guangdong-Hong Kong-Macao Greater Bay Area should re-understand and implement the national education right of the SAR, improve the standards and raining quality of talents, and strengthen innovation-driven development, and an education system with the characteristics of the Greater Bay Area should be built to give full play to the role of education in regional economic development and to cultivate talents in the new era. [ABSTRACT FROM AUTHOR]

Objective. To sort out the application and status quo of some domestic crowdsourcing models, explore the factors affecting multilingual manual annotation through experiments and offer suggestions. Methodology. Crawling the government news texts in Mandarin, Cantonese, English, and Portuguese in Guangdong, Hong Kong, and Macao, and enter them into the database. Combine it with corpus tagging uses the established web platform to practice crowdsourcing and collect a large number of annotation results and behavior data. Results. Made assumptions about factors that may affect the quality of manual annotation, used SPSS and other data analysis software to evaluate the degree of interpretation of the assumptions, provided a regression formula for calculating the accuracy, and provided constructive suggestions for the corpus annotation quality assurance projects. Limitations. More corpus information in more languages and more professional annotators are needed. Conclusions. The study found that the accuracy of annotation is strongly related to the attributes of the corpus itself, such as the total number of vocabularies, the number of rare words, the complexity of parts of speech, etc., and the condition of languages are different from each other. [ABSTRACT FROM AUTHOR]

Real-time modeling of regional troposphere has attracted considerable research attention in the current GNSS field, and its modeling products play an important role in global navigation satellite system (GNSS) real-time precise positioning and real-time inversion of atmospheric water vapor. Multicore support vector machine (MS) based on genetic optimization algorithm, single-core support vector machine (SVM), four-parameter method (FP), neural network method (BP), and root mean square fusion method (SUM) are used for real-time and final zenith tropospheric delay (ZTD) modeling of Hong Kong CORS network in this study. Real-time ZTD modeling experiment results for five consecutive days showed that the average deviation (bias) and root mean square (RMS) of FP, BP, SVM, and SUM reduced by 48.25%, 54.46%, 41.82%, and 51.82% and 43.16%, 48.46%, 30.09%, and 33.86%, respectively, compared with MS. The final ZTD modeling experiment results showed that the bias and RMS of FP, BP, SVM, and SUM reduced by 3.80%, 49.78%, 25.71%, and 49.35% and 43.16%, 48.46%, 30.09%, and 33.86%, respectively, compared with MS. Accuracy of the five methods generally reaches millimeter level in most of the time periods. MS demonstrates higher precision and stability in the modeling of stations with an elevation at the average level of the survey area and higher elevation than that of other models. MS, SVM, and SUM exhibit higher precision and stability in the modeling of the station with an elevation at the average level of the survey area than FP. Meanwhile, real-time modeling error distribution of the five methods is significantly better than the final modeling. Standard deviation and average real-time modeling improved by 43.19% and 24.04%, respectively. [ABSTRACT FROM AUTHOR]