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Understanding air quality requires a comprehensive understanding of its various factors. Most of the association rule techniques focuses on high frequency terms, ignoring the potential importance of low- frequency terms and causing unnecessary storage space waste. Therefore, a dynamic genetic association rule mining algorithm is proposed in this paper, which combines the improved dynamic genetic algorithm with the association rule mining algorithm to realize the importance mining of low- frequency terms. Firstly, in the chromosome coding phase of genetic algorithm, an innovative multi-information coding strategy is proposed, which selectively stores similar values of different levels in one storage unit. It avoids storing all the values at once and facilitates efficient mining of valid rules later. Secondly, by weighting the evaluation indicators such as support, confidence and promotion in association rule mining, a new evaluation index is formed, avoiding the need to set a minimum threshold for high-interest rules. Finally, in order to improve the mining performance of the rules, the dynamic crossover rate and mutation rate are set to improve the search efficiency of the algorithm. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the unit point multi-information coding strategy in reducing the rule storage air, the effectiveness of mining the rules formed by the low frequency item set, and the effectiveness of combining the rule mining algorithm with the swarm intelligence optimization algorithm in terms of search time and convergence. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the above three aspects. The unit point multi-information coding strategy reduced the rule space storage consumption by 50%, the new evaluation index can mine more interesting rules whose interest level can be up to 90%, while mining the rules formed by the lower frequency terms, and in terms of search time, we reduced it about 20% compared with some meta-heuristic algorithms, while improving convergence. [ABSTRACT FROM AUTHOR]

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules. [ABSTRACT FROM AUTHOR]

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, rainstorm and flood disasters have become the most serious cataclysm. Under the circumstances of an increasingly severe risk situation, it is necessary to enhance urban disaster resilience. Based on the disaster resilience process of prevention, absorption, and enhancement, and considering the safety factors such as personnel, facility, environment and management, this paper forms a dual dimension of the urban disaster resilience assessment model covering the key elements of urban disaster response and the core capacity of urban disaster recovery. Furthermore, if taking into account the characteristics of rainstorm and flood disasters, the paper screens the key indicators to build up an assessment index system of an urban rainstorm and flood disaster. The practical application was implemented in Beijing to have an assessment of the ability to recover from rainstorm and flood disasters in all districts of Beijing. And then, some pertinent suggestions for enhancing the resilience of Beijing to rainstorm and flood disasters were proposed. [ABSTRACT FROM AUTHOR]

In the process of development, global economies are prioritizing environmental protection and firms are also recognizing the importance of minimizing environmental impact during production along with maximization of profits through green investments. It is vivid that green investments are vital for environmental preservation. So this paper contributes to literature by investigating the role of internal and external factors affecting the decision making of Chinese firms regarding adoption of green investments and impact of green investments on environmental, social, and economic performance of firms. The data is collected from directors/senior managers of the firms. We received 463 valid responses from listed companies with Shenzhen, Beijing, and Shanghai Stock Exchange. The "structural equation modeling" with "maximum likelihood estimation" is employed for empirical analysis. The empirical findings reveal that adaptation to climate change and its mitigation is the most important driver of green investment. Moreover, green investment positively contributes to enhancing the social, economic, and environmental performances of Chinese firms. Based on the findings of the study, green investment should be adopted as a corporate strategy by firms for profit maximization, competitive advantage, and improvement in social well-being without compromising the environment. Policy makers can promote green investment by offering policy instruments such as tax incentives, guaranteed credits, grants, and investor education. Training courses may be offered to raise environmental awareness among firms and the general public. [ABSTRACT FROM AUTHOR]

The production connection is a crucial component of the Inter City Association. An urban network based on the enterprise perspective better reflects the structural characteristics of regional cities. Based on data gathered from the headquarters and branches of the listed manufacturing enterprises in 2020, this paper analyzes the county-level administrative units in the Beijing-Tianjin-Hebei region of China. Using the subordinate connection model and the social network analysis method, this paper examines the spatial structural characteristics and factors of urban networks in the Beijing-Tianjin-Hebei region. The results suggest that resource allocation in the Beijing-Tianjin-Hebei region is unbalanced, with a significant difference in urban radiation and agglomeration capacity. As the administrative centers, Beijing, Tianjin, and Shijiazhuang show a strong ability to allocate resources within the network. The overall network density in the region was shown to be relatively low, with the main links being of low or medium level. The urban network is defined by the network connection led by Beijing and Tianjin with Beijing-Tianjin-Tangshan and Beijing-Baoding-Shijiazhuang as the main axis. These cities exhibit a "dense southeast and sparse northwest" pattern. From a hierarchical perspective, high-level network connections are based mainly on spatial proximity. Analyzing the agglomerative subgroups, the study found that the inner and outer connections of the core subgroups were relatively high. Semi-marginal subgroups generally accepted the radiation of core subgroups, while marginal subgroups had little connection with other subgroups in the region. The results of the QAP analysis show that the administrative relationship, spatial distance, city size difference, economic development level difference, industrial structure difference, and labor cost difference have a significant influence on the urban network of the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

Industrial upgrading and transfer is one of the three key areas in the coordinated development of Beijing-Tianjin-Hebei Region. Meetings, incentives, conferences and exhibitions (MICE) are important means of promoting industrial upgrading. Urban MICE industry, as an important carrier of event activities, become an important gripper for coordinated development of Beijing-Tianjin-Hebei Region. City exhibition space structure plays an dominant role in regional economic development, and it will greatly promote smooth implementation of the coordinated development strategy of Beijing-Tianjin-Hebei Region. In this paper, 13 prefecture-level cities in Beijing, Tianjin and Hebei were selected as research objects, and the data from 2012 to 2018 were selected to establish a gravity model of the attractiveness of MICE cities. With the help of UCINET software, the network density, centrality, cohesive subgroup and core-edge of nodes researches were obtained to analyze the spatial structure characteristics of the attractiveness of MICE cities in Beijing-Tianjin-Hebei Region. The influencing factors of the spatial characteristics of MICE city attractiveness are analyzed by using geographically weighted regression model. The results show that: (1) Beijing, as the overall core area, act as a prominent role. Beijing strengthens the attraction to the superior resources of the surrounding areas, but the network of MICE cities tends to be unbalanced. (2) Overall space forms a subgroup from a single independent subgroup to a subgroup that is spatially separated from each other and acts as an intermediary channel to connect each other, and the core region decreases from 3 to 2. Langfang was removed from the list, leaving Beijing and Tianjin as the core. (3) The influence of supporting facilities, urban environment and population factors on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is increasing gradually. The influence of tourism development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is decreasing gradually. The influence of economic development level and Internet development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region remains unchanged. [ABSTRACT FROM AUTHOR]

Whether the place-based industrial policy promotes regional economic growth is a hot issue in the field of regional industrial economic practice. As a major national strategy in China, the Beijing-Tianjin-Hebei industrial coordinated development policy has been implemented more than 8 years. Verifying its effect on regional economic growth and revealing the policy action path will help to further optimize the policy implementation process through feedback. In this paper, the policy effect and its differentiation are empirically studied from 'quality' and 'quantity' respectively by establishing a growth model using the Dual Differences method. The results show that the Beijing-Tianjin-Hebei industrial coordinated development policy improves total factor productivity by 2.26% in terms of 'quality', and reduces GDP growth rate by 4.65% in terms of 'quantity'. For the different region, the GDP growth rate increased by 1.28%, while total factor productivity decreased by 2.63% in Beijing, the GDP growth rate decreased by 3.17% and total factor productivity increased by 0.87% in Tianjin, and the GDP growth rate increased by 2.56% and total factor productivity increased by 1.58% in Hebei. The policy is mainly realized by fixed asset investment, capital deepening degree and enterprise scale expansion, while the effect of labor input, R&D investment and enterprise number is not significant. The policy is to give full play to the driving role of fixed asset investment such as "new infrastructure", increase investment in labor and research and development in the region, strengthen the construction of a competitive market environment, and stabilize the 'quality' and 'quantity' to further release policy dividends. [ABSTRACT FROM AUTHOR]

After the cold war, some countries gradually seek to regional cooperation when they could not handle various transnational challenges alone. Shanghai Cooperation Organization (SCO) is a good example. It brought Central Asian countries together. This paper applies the text-mining method, using co-word analysis, co-occurrence matrix, cluster analysis, and strategic diagram to analyze the selected articles from newspapers quantitatively and visually. In order to investigate the Chinese government's attitude toward the SCO, this study collected data from the China Core Newspaper Full-text Database, which contains high-impact government newspapers revealing the Chinese government's perception of the SCO. This study characterizes the changing role of SCO as perceived by the Chinese government from 2001 to 2019. Beijing's changing expectations in each of the three identified subperiods are described. [ABSTRACT FROM AUTHOR]

This paper constructs a matching index model to research the matching degree of embodied carbon trade and value-added trade among eight regions and 31 provinces in China in 2012 and 2015. The study finds that (1) At the regional level, a mismatch is shown between embodied carbon trade and value-added trade among regions, for example, in 2015, the northwest region has output embodied carbon to the north coast, while input the value-added trades from the north coast. (2) At the provincial level, a mismatch is displayed between embodied carbon transaction and value-added trade, for example, Beijing had a net shift of embodied carbon from Xinjiang in 2015, but Xinjiang had a net transfer of added value from Beijing. Therefore, the Chinese government needs to establish an ecological compensation mechanism to improve the mismatch between embodied carbon trade and value-added trade among Chinese regions (provinces). [ABSTRACT FROM AUTHOR]

COVID-19 leads small and medium-sized enterprises (SMEs) to survive very hard. The development difficulties of SMEs lead to weak employment and GDP growth in various countries. In the process of COVID-19's continuous spread, what is the major reason for the difficulties of SMEs? This paper hopes to answer this question by studying SMEs in Beijing. On this basis, this paper uses structural equation model (SEM) to study the relatively fast recovery of SMEs in Beijing, China, to explore the factors affecting SMEs in the pandemic. After detailed desk research and interviews with relevant entrepreneurs, this paper collects 234 valid questionnaires from SMEs in various industries in Beijing with the help of Federation of Industry and Commerce and Chamber of Commerce in Beijing. Then the data is analyzed with the SEM, which shows the relationship between cash flow from financing activities, markets, employees, costs, government policies and the impact of the pandemic. Finally, an impact model of the pandemic on SMEs is established. The result of the model indicates that the direct effect of the pandemic on the market is the most prominent, and government policies can significantly reduce the negative impact of the pandemic on SMEs indirectly. Based on this, this paper puts forward some policy suggestions, such as the targeted issuance of consumption vouchers and the reduction of administrative barriers. This will enable megacities in various countries to improve policy support for SMEs and promote the recovery and development of SMEs. [ABSTRACT FROM AUTHOR]

Depending on the strategy of "Healthy China", more and more people pay attention to health issues. The integration and development of sports industry and health service industry is an inevitable outcome of industrial transformation and upgrading and healthy life in the new era. Through constructing the evaluation index system of the coupling and coordination development degree between sports industry and health service industry, using entropy evaluation method and coupling and coordination degree model, this paper explore the comprehensive level and coupling and coordination development status of sports industry and health service industry in thirty-one provinces, municipality cities and autonomous regions of China from 2013 to 2017. The results of this paper show that the comprehensive China's sports industry and health service industry both present an incremental development trend year by year, and are characterized by the distribution of "high in the east and low in the west" in space. The government's policy support provides superior industrial supporting conditions for the development of sports industry. However, it is not conducive to the promotion of industrial economic benefits. In the health service industry, the rapid development of health insurance is beneficial to the integration of industrial resources and the perfection of industrial chain. Whereas as the core content of health service industry, health service has greater space for development; the coupling and coordination degree between the two industries rises from mild maladjustment to basic coordination, which is characterized by the distribution of "high in the east and low in the west" in space; among provinces, with Beijing, the Yangtze River Delta and Guangdong as the three development center points, it shows the spatial evolutionary process from "dispersion-type plaques" to "gathering type scattered surfaces". [ABSTRACT FROM AUTHOR]

Beijing plain is a strong earthquake tectonic area in China. There was a Sanhe-Pinggu earthquake with Ms8 that happened in1679. The seismogenic fault of this earthquake is called Xiadian fault. Our work found fault with a similar strike and opposite dip in the west of the Xiadian fault, which is called the Xiadian west fault in this paper. Six shallow seismic profiles have been constructed to determine the location of the fault in Sanhe city, and the late Quaternary activity of the fault is studied with the method of combined drilling, magnetic susceptibility logging, and luminescence dating. The results of shallow seismic exploration show that the fault is zigzag and generally strikes NE and inclines NW. According to the core histogram and logging curves of ten boreholes and eight effective dating data, the buried depth of the upper breakpoint of the concealed fault is about 12 m, which dislocates the late Pleistocene strata. The effective dating result of this set of strata is 36.52 ±5.39 ka. The vertical slip rate has been about 0.075± 0.023 mm/a since the late Pleistocene and about 0.058 ± 0.030 mm/a since the late period of the late Pleistocene. It can be inferred that the Xiadian west fault is probably a part of the seismogenic structure of the Sanhe-Pinggu Ms8 earthquake that happened in 1679. In a broad sense, the Xiadian fault zone is likely to extend to the southwest along the Xiadian west fault. [ABSTRACT FROM AUTHOR]

In regional land-use planning, many different demands for often-limited land resources must be weighed against each other. Analysis of the benefits of different land-use types is of great significance in land-use design. However, a good evaluation methodology does not exist. To facilitate a comparative analysis of land-use benefits, this paper presents an evaluation system consisting of four steps: (1) Connotation dissection to determine the land-use benefits, (2) construction of a land-use benefit classification system to summarize a limited number of land-use benefit types by an inductive method, (3) land-use benefit valuation, which includes a biophysical model, direct and indirect market valuations, and The Economics of Ecosystems and Biodiversity value conversion method, and (4) case analysis of the evaluation results according to local conditions. Empirical results from a case study of Mentougou District, Beijing, China, show that (i) the evaluation results of land-use benefit groups provides information on each land-use type and the spatial distribution of land-use benefits in Mentougou District, (ii) the topography of Mentougou District has an important influence on economic and ecological land-use benefits, and (iii) there is a synergistic effect of economic and social land-use benefits. [ABSTRACT FROM AUTHOR]

The transportation industry has entered a new stage from quantity expanding to structure optimization, quality and efficiency improvement, and from respective governance to integrative development. This indicates that the traditional corridor mode allocation dominated by quantity equilibrium can no longer meet the requirements of the new stage. In this paper, we propose a multi-entity programming model based on the economic equilibrium between supply and demand. It not only ensures the economic equilibrium in the market, but also maximizes the social benefits of the whole system, thereby realizing the sustainable development of the transportation system. Also, the Globalsearch algorithm and intlinprog algorithm are designed to solve the problem. The actual case of Beijing-Shanghai corridor shows that the model and algorithms are effective, providing decision support for the optimal allocation of regional transport network resources. [ABSTRACT FROM AUTHOR]

This paper examines whether mega-events-initiated planning regulations improved air quality in Chinese cities and explores the driving forces of the enforcement of such regulations. Using the 2008 Beijing Olympics as an example, we find that mega-events serve as an opportunity for cities to combat air pollution. The 2008 Olympics prompted a handful of Chinese cities to cut pollution and sustain a blue sky: Cities with air quality regulated for the Olympics cut their Air Pollution Index by about 16 points during the Games, compared to non-regulated cities, and 60% of that effect remained four years after the event. These achievements are obtained through effective mobilization of city leaders by associating air quality with their political careers. This study reveals that 1) a mega-event may improve urban environmental quality beyond the host cities and the event period, and 2) successful implementation of environmental regulations hinges on incentivizing local leaders. [ABSTRACT FROM AUTHOR]

Through the online booking platform, 10,543 big data of spatial and temporal distribution of Beijing hotel industry has been obtained in this paper. Then, the methods of GIS and the geographical detector are used to study the spatiotemporal evolution process and the influencing factors of Beijing hotel industry during 2003–2018. The results are as follows: a. During the period of 2003–2018, the hotel industry in Beijing maintained a high growth rate and had three growth peaks in 2008, 2010 and 2014. Meanwhile, major historical events, such as the Olympic Games had a significant influence on the development of the hotel industry. b. Between 2003 and 2018, the hotel industry in Beijing gradually developed from the centripetal agglomeration to aggregation + diffusion, and also from the single center to the multi-center. Besides, various hotels presented two characteristics of city orientation and scenic orientation. c. The natural geographical environment had shaped the overall pattern and characteristics of the spatial distribution of the hotel industry in Beijing, and the socio-economic factors such as commercial activities, public facilities, tourism services and traffic conditions significantly influenced the location selection of the hotel industry. Therefore, the urban center is the ideal area for the spatial layout of the hotel industry. d. Geographical detector research showed that the factors, such as administrative organs, road network density, leisure and recreational facilities, and companies have strong explanatory power for hotel location selection, which is an important reference index for hotels to select the micro location. This paper is a beneficial supplement to the existing research and has certain guiding significance for the sustainable development of Beijing hotel industry. [ABSTRACT FROM AUTHOR]

Over exploitation of groundwater in Changping District of Beijing city has caused serious land subsidence in the past decades. In recent years, the operation of the South-to-North Water Transfer Project has reduced the land subsidence rate. In this paper, Experimental tests are performed using the GDS Consolidation Testing System to characterize the compression and rebound of soils at depths of less than 100 m caused by groundwater withdrawal and recharge in Changping District. The results indicate that the compressible layers are the main contributors to land subsidence. The first compressible layer experiences greater deformation and more considerable hysteresis than the other compressible layers with the same decrease in the pore water pressure. Therefore, the exploitation of the adjacent aquifer should be controlled in the future. The deformation in the second and third compressible layers is a gradual and long-term process with little rebound; therefore, the subsidence should be seriously addressed when the groundwater in the two compressible layers is exploited on a large scale. In the same compressible layer, silty clay is more compressible and hysteretic than silt. For the same soil sample, the deformation rate decreases gradually as the pore water pressure decreases, whereas the creep deformation shows an overall increasing trend. A parameter named the subsidence index Cw is proposed in this paper to describe the soil compressibility during groundwater withdrawal. All the soil samples are characterized by elastic-plastic deformation, and the shallow soil samples with less pore water pressure decrease are more likely to rebound. [ABSTRACT FROM AUTHOR]

China has set a goal to achieve peak CO2 emissions before 2030 and carbon neutrality by 2060. To achieve the goals of carbon peak and carbon neutrality, China needs to address the challenge of the large and still growing CO2 emission base. This paper investigated the energy consumption and CO2 emission in Beijing from 2020–2035 based on the energy elasticity coefficient and contribution value of the sub-energy increment (CVSI) method. Beijing is one of the first cities in China to propose the "carbon peak" target as of 2020. From 2020 Beijing will strive to achieve the goal of carbon neutrality. The results show that in 2035 the CO2 emission in Beijing may drop to 50% of 2020. This decline would be affected by economic growth, energy efficiency and the proportion of renewable energy use. Beijing's energy supply mainly comes from outside the region. Therefore, for Beijing, in addition to increasing the proportion of renewable energy sources outside the region, its own energy acceptance also needs to be strengthened, including strengthening energy storage construction, actively researching and promoting carbon capture and utilization of gas-fired units, which are effective ways to achieve carbon neutrality target. [ABSTRACT FROM AUTHOR]

How to promote and improve the level of urban innovation cooperation is a major issue in China's current high-quality economic development. Thus, enhancing innovation ability is essential to achieving high-quality economic growth under the "new normal". Based on the data of Chinese invention patents from 1985 to 2017, this paper analyzes the characteristics of China's urban innovation cooperation network and the different roles of proximity by using social network analysis and exploratory spatial data analysis methods. The analysis results show that: (1) On the whole, the development of China's urban innovation cooperation network is characterized by stages (initial development stage, rapid development stage, and gradual decline stage); The urban innovation cooperation network has strong connectivity and centripetal concentration but its imbalance needs to be further improved; The degree of urban participation has gradually increased, consolidating the stability of the network structure. (2) The centrality of urban innovation cooperation network has obvious characteristics of administrative center orientation, coastal areas orientation, and 'strong east and weak west'; Beijing is the center and bridge of the network, and the network flattening characteristics are obvious; A hierarchical 'core-edge' structure is gradually formed for the urban innovation cooperation network, and the pyramid structure with Beijing standing at the top is being consolidated. (3) The geographical proximity presents a significant global spatial positive correlation, while the network proximity and pure network proximity have a more significant global spatial negative correlation; The local spatial autocorrelation of China's urban innovation cooperation system based on network proximity is more obvious and identifiable than that based on the geographical proximity, which better reflects the new development model of "relationship economy". [ABSTRACT FROM AUTHOR]

Household time-use patterns are expected to reflect each household member's daily activity participation and duration with intra-household interactions constrained by multiple budgets. Among various activities, the allocated activity derived from undertaking a household task is studied relatively less in the literature. Who will take an allocated activity is a discrete choice problem of household task assignment, and once a household member is assigned with one household task, other members will have more time to do other activities. To better understand household time-use patterns affected by household task assignment, this paper proposed a joint household-level multiple discrete-continuous extreme value-multinomial logit (MDCEV-MNL) model with multiple constraints. The Karush-Kuhn-Tucker (KKT) method combined with the simulation-based maximum likelihood estimation method is proposed to estimate the proposed model. Based on the household activity-travel data from Beijing of China, the proposed model is customized to explore elderly couples' time-use patterns with intra-household interactions affected by household task assignment. Following the findings, policy implications are suggested to build an age-friendly society. [ABSTRACT FROM AUTHOR]

As the capital and one of the metropolises in China, Beijing has met with a number of serious so-called "urban diseases" in the process of rapid urbanization such as blind expansion of urban areas, explosion of population and the increase of urban heat island effect. To treat these "urban diseases" and make the metropolis develop healthful and sustainable in Beijing in the future, the spatial characteristics of metropolis developments in Beijing are explored in this paper. The urban built-up areas in Beijing are extracted using the DMSP-OLS nighttime light data from 1992 to 2013. The characteristics of the urban developments of Beijing are studied, including spatial and temporal scales of urban developments, urban barycenter of Beijing and its transfer trajectory, variations of urban spatial forms and the differences of urban internal developments. The results have shown that the built-up areas had been increasing and circling extending from the central urban areas to the outer spaces in the last 21 years. The built-up area had expanded by 878km2 in 1992–2013, and the built-up area in 2013 had expanded to three times comparing to that of 1992. The expanding area of the built-up area in the northeast is the largest. The expansion of the urban had mainly occurred in 1996–2007, and the expanded area had accounted for 92% of the total research period. During the whole research period, the urban barycenter of Beijing had moved 5000.71 meters towards Northeast 28° of its original place from Dongcheng District to Chaoyang District. The development level of each municipal district had been increasing year by year, and the development differences among the municipal districts had been gradually reduced; the spatial forms of Beijing had been alternately changed between extensive and intensive expansion. The results of this study can help to plan urban land use and people migration of Beijing. [ABSTRACT FROM AUTHOR]

Recent advance in VMS technology has made it viable to ease traffic congestion and improve road traffic efficiency. However, the drivers' low compliance with the posted information may limit its performance to ease traffic congestion and improve traffic safety. This paper explores drivers' attitude to the service quality of VMS system resulted from the identified predominant influencing factors. A questionnaire is developed and used for surveying 9,600 drivers in Beijing, China. The collected data are analyzed with a multiple indicators and multiple causes (MIMIC) model considering different driver categories (e.g., private car driver, office car driver, taxi driver). The results show that the causal relationships between latent variables and socio-demographic characteristic is significant. Driving frequency, attitude towards contents of VMS, drivers' decision-making and the effectiveness of VMS message can directly and indirectly affect driver's perceived quality of service. The attitude towards formats of VMS indirectly affect their QoS resulting from the effectiveness of VMS message, while there is no indirect impact for taxi drivers. Besides, the drivers' decision-making directly affects the perceived quality of service for private car drivers and office car drivers, but there is no impact for taxi drivers. The findings of this study can provide guidance and reference for urban authorities to perform the relevant actions required to meet user expectations. [ABSTRACT FROM AUTHOR]

Small public spaces are the key built environment elements that provide venues for various of activities. However, existing measurements or approaches could not efficiently and effectively quantify how small public spaces are being used. In this paper, we utilized a deep convolutional neural network to quantify the usage of small public spaces through recorded videos as a reliable and robust method to bridge the literature gap. To start with, we deployed photographic devices to record videos that cover the minimum enclosing square of a small public space for a certain period of time, then utilized a deep convolutional neural network to detect people in these videos and converted their location from image-based position to real-world projected coordinates. To validate the accuracy and robustness of the method, we experimented our approach in a residential community in Beijing, and our results confirmed that the usage of small public spaces could be measured and quantified effectively and efficiently. [ABSTRACT FROM AUTHOR]

To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system. [ABSTRACT FROM AUTHOR]

The effectiveness of rapid rail transit system is analyzed using tools of complex network for the first time. We evaluated the effectiveness of the system in Beijing quantitatively from different perspectives, including descriptive statistics analysis, bridging property, centrality property, ability of connecting different part of the system and ability of disease spreading. The results showed that the public transport of Beijing does benefit from the rapid rail transit lines, and the benefit of different regions from RRTS is gradually decreased from the north to the south. The paper concluded with some policy suggestions regarding how to promote the system. This study offered significant insight that can help understand the public transportation better. The methodology can be easily applied to analyze other urban public systems, such as electricity grid, water system, to develop more livable cities. [ABSTRACT FROM AUTHOR]

This paper develops a methodology for extending multilevel modelling to incorporate spatial interaction effects. The motivation is that classic multilevel models are not specifically spatial. Lower level units may be nested into higher level ones based on a geographical hierarchy (or a membership structure—for example, census zones into regions) but the actual locations of the units and the distances between them are not directly considered: what matters is the groupings but not how close together any two units are within those groupings. As a consequence, spatial interaction effects are neither modelled nor measured, confounding group effects (understood as some sort of contextual effect that acts ‘top down’ upon members of a group) with proximity effects (some sort of joint dependency that emerges between neighbours). To deal with this, we incorporate spatial simultaneous autoregressive processes into both the outcome variable and the higher level residuals. To assess the performance of the proposed method and the classic multilevel model, a series of Monte Carlo simulations are conducted. The results show that the proposed method performs well in retrieving the true model parameters whereas the classic multilevel model provides biased and inefficient parameter estimation in the presence of spatial interactions. An important implication of the study is to be cautious of an apparent neighbourhood effect in terms of both its magnitude and statistical significance if spatial interaction effects at a lower level are suspected. Applying the new approach to a two-level land price data set for Beijing, China, we find significant spatial interactions at both the land parcel and district levels. [ABSTRACT FROM AUTHOR]