Stations In Area Research Articles

Predicting and assessing greenhouse gas emissions during the construction of monorail systems using artificial intelligence.

Based on partial data, this paper uses BP neural network optimised by particle swarm optimisation algorithm to predict the total greenhouse gas (GHG) emissions of the line in the construction phase. The GHG emission efficiency is analysed by SBM (Slacks-Based Measure) super efficiency method. Finally, the grey relational analysis (GRA) is applied to sort the GHG emission correlation factors. Based on the existing design and quota document data of 16 stations and 16 sections of the Wuhu Monorail Line 1, we have employed a neural network optimized by particle swarm optimization algorithm to predict the total emissions of greenhouse gases during the construction phase of the entire line consisting of 25 stations and 24 sections. The GHG emissions of all stations and sections are 29,300 tons and 21,000 tons. The technical efficiency, pure technical efficiency, and scale efficiency of the stations and sections were high. As for stations, the order of influence degree is metal material consumption (0.9731) > cost (0.9486) > electric energy consumption (0.9481) > station area (0.9109) > concrete and cement consumption (0.9032) > other material consumption (0.8831) > gasoline and diesel consumption (0.7258). For the section, the order of influence degree is cost (0.9766) > concrete (0.9581) > steel reinforcement (0.9483) > other steels (0.874) > section length (0.8337) > power energy consumption (0.7169) > wood consumption (0.6684).

Confidence relative off-targets distance-based multi-dimensional transparency evaluation of distribution station area

With the large-scale integration of distributed renewable energy into low-voltage distribution station areas, rapidly growing services put forward new requirements on transparent monitoring. In order to accurately and objectively quantify the transparency of various distribution station areas and measure the impact of different dimensional indexes on the transparency evaluation of distribution station areas, this paper proposes a confidence relative off-target distance-based multi-dimensional transparency evaluation method. First, a multi-dimensional transparency evaluation index system with electrical and communication integration is constructed. Second, an improved gray target model combining both positive and negative target vectors is established to realize bi-directional quantitative analysis. Then, the relative off-target distance is calculated based on the endowment coefficient by leveraging both subjective and objective weights. Finally, the confidence of the relative off-target distance is calculated based on fuzzy entropy to improve the reliability of transparency evaluation. The simulation results show that this method can effectively distinguish the transparency gap between different distribution station areas, identify the single dimensional index with the greatest contribution or potential, and verify the effectiveness of the proposed method applied to the transparency evaluation of distribution station areas.

Evaluating changes in business distribution within urban rail transit hubs in Beijing via Point of Interest (POI) data analysis (2008–2020)

This paper, set against the backdrop of expanding urban rail networks and dynamic urban development, focuses on the distribution and evolution of commercial Points of Interests (POIs) within the central urban rail transit areas of Beijing. The study examines data from four different years—2008, 2013, 2017, and 2020—to observe the temporal evolution of commercial entities. It identifies stable explanatory variables affecting the distribution and evolution of commercial POIs, which include rail transit accessibility, characteristics of the working and residential population distribution around stations, and the construction intensity in the vicinity of station areas. Through statistical analysis and model building, relatively stable linear regression equations were established, with R2 values generally maintained above 0.5 (except for 2017). The study advances our understanding of the influence of rail transit on urban commercial spaces and how this influence shifts with temporal and urban developmental changes. It elucidates the correlation between changes in the number of businesses and spatial configuration, offering insights and information for urban planners and policy makers. This research also serves as a model for exploring the interplay between urban rail transit and commercial spaces in other major cities.

Evaluate Human Perception of the Built Environment in the Metro Station Area

Transit-oriented development (TOD) has become a dominant form of spatial planning and land use in large cities internationally. As the intersections of urban space and rail transportation, metro station areas play a key public service function in the lives of city residents. Based on the “5D” index and Node-Place theory in the metro station area, current research on the built environment in metro station areas focuses on improving the economic and transportation efficiency while neglecting public perception of the construction of station space. Sentiments, as an important part of the individual’s perception, are closely related to the built environment. Therefore, this study takes 187 metro stations within the fifth ring road of Beijing, China, as an example and extracts public sentiment information from social media data using a wide range of natural language processing techniques to quantitatively analyze the distribution of the public’s sentiment characteristics (including intensity, polarity, and category) in the metro station area and deeply explores the spatial correlation with the distribution of the objective built environment elements. The study shows that influenced by the spatial design of the metro station, density, land use functions, etc., the sentiment intensity of the station area within the Fifth Ring Road of Beijing is “strong in the east and weak in the west, strong in the north and weak in the south”, and the sentiment polarity has the characteristic of gradually negative from inside to outside in a circular pattern. Synthesizing the sentiment perception in the metro station area, our study further divided the Beijing metro station area into four major categories and eight specific subtypes.

Precipitable water characterization using global navigation satellite system data: A case study in Nghia Do area, Vietnam

This paper evaluates the estimated total precipitable water (TPW) and studies its characteristics in the Nghia Do area (Hanoi) using Global Positioning System (GPS) data and the Canadian Spatial Reference System-Precise Point Positioning (CSRS-PPP) processing technique and calculation tool. The TPW was estimated from GPS data from September 22, 2022 to March 31, 2023 using CSRS-PPP provided by Natural Resources Canada. The calculated TPW was validated with TPW products from Aeronet data and radiosonde data. Taking advantage of its high time resolution, the TPW estimated from GPS data was used to analyze the temporal variation of TPW during cold surges affecting the Nghia Do area. The results indicate a strong agreement between the estimated TPW from GPS data and TPW products derived from Aeronet and radiosonde data. The mean error (ME), root mean square error (RMSE), and correlation coefficient between the estimated TPW from GPS data and the Aeronet-derived product are 0.68 mm, 2.05 mm, and 0.988, respectively. The corresponding values between the estimated TPW and the radiosonde-derived product are -3.01 mm, 3.24 mm, and 0.996, respectively. The study of TPW variation over the Nghia Do area during the research period revealed that, generally, TPW values in December and January were lower than those in the other months. Before the arrival of a specific cold surge at a station, TPW tends to increase by about 6 mm within 12 hours as convection activities ahead of the cold front intensify. After the cold air passes over the station, the TPW value decreases by about 8 mm within 12 hours due to the influx of cold and dry winter air brought by the prevailing winds. This distinct TPW variation pattern suggests that GPS data can be effectively employed to define the arrival of cold surges in the station area.

A comparative study on walking accessibility of high-speed railway station areas in China and Japan based on analytic hierarchy process -- Beijing station and Osaka station as examples

ABSTRACT To capture the factors influencing and measurements of pedestrian accessibility to high-speed rail station areas, ensure the balance between the transportation function and place performance of high-speed railway station areas, the correlation factors and laws of pedestrian space characteristics of high-speed railway station areas under different development modes are studied through the comparison of typical high-speed railway station areas in China and Japan. Combining the circle law and hierarchical analysis method, we establish a walking accessibility index system, construct a walking accessibility evaluation model for the high-speed rail station area, measure the degree of walking accessibility in the high-speed rail station area, and analyze the influence mechanism of different walking space components on the walking accessibility of the high-speed rail station area circle. The results indicate that: 1) Osaka Station space is much more walkable than Beijing Station in all circles; 2) The spatial development within the Beijing Station Station Circle is uneven, and the degree of pedestrian accessibility decreases as the circle’s extent increases; 3)Different station spaces have their own advantages and disadvantages in terms of the distribution of public facilities and amenities, roadway attributes, pedestrian path characteristics, depending on their respective national conditions and station development patterns.

Research on a new management model of distribution Internet of Things

Based on the characteristics of controllable intelligence of the Internet of Things (IoT) and the requirements of the new distribution Network for function and transmission delay, this study proposes a method of combining edge collaborative computing and distribution Network station area, and builds a distribution Network management structure model by combining the Packet Transport Network (PTN) Network structure. The multi-terminal node distribution model of distributed IoT is established. Finally, a distribution IoT management model is constructed based on the edge multi-node cooperative reasoning algorithm and collaborative computing architecture model. The purpose of this paper is to solve the problem of large reasoning delay caused by heavy computing tasks in distribution cloud servers. The final results show that the model reduces the inference delay of cloud computing when a large number of smart device terminals of distribution IoT are connected to the network.

Contributions of the vegetation index (NDVI) in water quality prediction models in a semi-arid tropical watershed

In this work, a new approach to using NDVI as a predictor of water quality parameters in arid environments is proposed. Our focus was the Araçuaí river basin, which has a predominance of native cerrado vegetation and is subject to seasonal variations in rainfall and vegetation cover. MODIS images (MOD13Q1) from 2000 to 2018 were used to calculate the NDVI of the contributing areas of the water quality monitoring stations and to analyze its relationship with fourteen water quality parameters. The NDVI showed significant seasonality, with high values in the rainy season, and temporal trends of increase in stretches related to the main river. A strong and new relationship was observed between NDVI and six water quality parameters: color, total dissolved solids, total suspended solids, total solids, nitrate and turbidity, this being stronger at the local scale, with better performance at from models that use incremental NDVI, capturing local variations in vegetation cover, instead of regional NDVI, which reflects the general state of vegetation. The results demonstrate the potential of using these indices to develop and improve prediction models of water quality parameters in river basins and to expand the spatial and temporal coverage of water quality monitoring.

Failure Analyses on a Flexible Anode Cathodic Protection System in a Station.

Flexible anodes are a common form of anode ground bed for the cathodic protection of buried pipes in station areas, especially in new stations. In most cases, flexible anode ground beds could obtain uniform potential distribution and good protection. However, in the process of operation, there are also failure conditions such as anode body or cable breakage, electronic shorting between anode and pipes and other situations, resulting in poor protection. How to troubleshoot failures has become a difficult problem restricting the application of flexible anodes in actual production. In this paper, the failures of a flexible anode cathodic protection system in a station were assessed and analyzed in detail. The main reasons for the failures were the electronic shorting between the flexible anode and buried pipe in local area and the breaking of a partial flexible anode. The troubleshooting methods for two kinds of failures were explored. By measuring the potentials of both the flexible anode and pipes in different areas and the excavation test, the location of electronic shoring was determined. And through measuring the grounding resistance of the flexible anode and excavation test, the breaking location of the flexible anode was found. By repairing the failure sites, the failed system was restored to normal, which could provide guidance for the failure analyses of the flexible anode cathodic protection system.

EVALUASI KINERJA LALU LINTAS PEMBANGUNAN UNDERPASS CIBITUNG KABUPATEN BEKASI DENGAN MENGGUNAKAN APLIKASI VISSIM (Kawasan Pasar Induk dan Stasiun Cibitung Kabupaten Bekasi)

Bekasi District is one of the areas of the national economy that has a significant influence on the industrial sector. A large number of generation and attraction areas occur in the Main Market and Cibitung Station areas. The main market is a generation and pull area for people from inside or outside Bekasi Regency, while the Cibitung Station area is a new zone that is the generation and pull area for Jabodetabek commuter trips. One of the improvement activities in Bekasi Regency is the construction of the Cibitung Underpass. This underpass is located on Jalan Bosih Raya as a solution to traffic congestion in the Cibitung Station area. The existence of this underpass should provide a solution to congestion in the Pasar Induk and Cibitung Station areas, but if seen at this time the traffic conditions in the Cibitung Main Market Area are still experiencing congestion. The method used in this research is to create a validated traffic network model with the help of Vissim software. The model is then used to determine the performance of traffic sections and intersections both in terms of current conditions and in terms of the handling process. the optimization of the intersections were calculated using the MKJI model. Traffic performance of road sections and intersections will be obtained from alternative treatments. The expected research result is to get the best alternative that is able to reduce the value of queues and delays in the study area.

Analysis of place function and spatial distribution on HSR station area: A case study of Jinanxi Station

The HSR station area not only assumes the function of the city’s external communication, but also is an important public space, which plays an important role in the urban development. Based on the relevant theories, this paper analyzes and evaluates the status quo of the site functions in the Jinanxi Station area by combining the on-site survey and POI data. It is concluded that the site functions in the Jinanxi Station area are formed relatively slowly, with strong characteristics of circle structure and single residential function, showing unbalanced characteristics, but it will have huge space for future development. So in order to achieve an integrated development between station and city, it should avoid a single residential function, and achieve diversified functional development, require planning guidance and government guidance as well as further support and orderly promotion of policy funds.

The Relationship between Built Environment Characteristics and Metro Stations Pedestrian Catchment Areas

The study of pedestrian catchment areas for metro stations serves as the foundation for addressing issues such as‐passenger flow forecasting, land use planning around stations, and transportation link facility planning. This study aims to investigate how various factors related to pedestrians, the environment, and the characteristics of metro stations affect the areas where pedestrians are attracted to. The goal is to gain insights into design strategies and policy interventions that can enhance the appeal of metro stations. The present study considers the metro stations in the Chengdu area as the primary research objects. A framework for examining the connection between the built environment and the pedestrian catchment area of a subway station through the use of a hybrid gradient decision tree approach has been used. The study examines the pedestrian catchment areas of these stations and confirms the presence of a nonlinear relationship between pedestrian catchment areas and variables at these stations. There exists a negative correlation, within specific thresholds, between the number of companies, bus stops, and road network density with the catchment area of passengers. Concurrently, there is a positive correlation between the distances to the city center and the catchment area. Furthermore, this framework, which accounts for spatial heterogeneity, showed significant goodness‐of‐fit and predictive capability, aspects that were overlooked in earlier research. As a result, these research findings can serve as a key foundation for advancing the theoretical framework and statistical proof to facilitate land planning and development near metro stations, predicting passenger flow, and designing essential connecting amenities in the vicinity of such facilities.

Development of a portable retractable tower naming plate paster

Due to the use of the new line and the new station area, the existing tower naming plate has not met the requirements of the latest specification, and it is urgent to replace it in batches, but the traditional naming plate pasting work must be carried out manually throughout the whole process, which is time-consuming and laborious, and the efficiency is low. In order to solve the above problems, a portable retractable tower naming plate pasting device was developed to improve the on-site pasting working mode, and the device integrates a fixed fixture, a cleaning brush, and a retractable insulating rod in one, and has the characteristics of portability and high efficiency. It has been proved in practice that the developed device can effectively reduce the unqualified rate of pasting and improve work efficiency, and effectively improve quality and efficiency.

Data analysis and calibration of substation monitoring system based on Internet of Things (IoT)

Abstract The complex correlation of multi-source information of power equipment and the efficient validation of data information in the context of the Internet of Things (IoT) of electric power need to be studied urgently. The study applies density clustering to simplify the connection between multidimensional data and proposes a method for detecting anomalies in power equipment states based on interval set theory and density clustering. In addition, to ensure the accuracy of protection and measurement data for secondary equipment in substations, a dual verification system is established to sample secondary equipment data in the station area. The results of the related case study show that the anomaly detection method applying interval set clustering analysis can quickly and effectively detect the state anomalies of power equipment, which can be used as a decision-making basis for power grid troubleshooting. Based on the double calibration system of the guaranteed measurement data, it can realize the functions of power metering device error calibration, a secondary load test of the transformer, a voltage drop test of the secondary circuit of the voltage transformer, and so on.

Line loss localization diagnosis and management measures of station area combined with data mining

Abstract This study explores an advanced method for improving line loss in station areas, a vital issue in the energy sector. By analyzing line loss data from the X-area station using data mining and a novel convolutional neural network (CNN) model optimized with particle swarm optimization, we aimed to pinpoint and diagnose line loss issues effectively. Our model, which integrates specific line loss predictive parameters, underwent rigorous training and testing with collected data. The results were promising: the model's predictions closely matched actual data, with most errors under 0.1. It outperformed existing models in iteration speed, convergence time, and accuracy, evidenced by lower mean square error (0.0112), root mean square error (0.1023), and average absolute error (3.2514%). This research presents a potent tool for distribution network analysis, offering practical insights for line loss localization and diagnosis.

ЧАСТОТНО-ТЕРРИТОРИАЛЬНОЕ ПЛАНИРОВАНИЕ ТРАНКИНГОВЫХ СИСТЕМ СВЯЗИ

The article considers the design of a trunking communication system using the proposed method of automatic placement of base stations and the developed software. The aim of the work is to reduce the complexity of designing trunking communication systems. In the automatic placement method, special attention is paid to calculating the required number of channels for organizing communication between a given number of subscribers. The scientific novelty of the presented solution lies in the fact that in the method of automatic placement of base stations, the coordinates of their installation locations are determined using the proposed greedy algorithm, in which the calculation of the service areas of base stations is carried out on the basis of a modified Hut model. Then, for the obtained coordinates of the base station installation sites, an updated calculation of the service areas is carried out, taking into account additional diffraction losses, tropospheric scattering and losses in the atmospheric waveguide. After that, the guaranteed service area is determined. The results of the design of the trunking communication system in the developed software are presented, graphs of the dependence of the calculation time of the greedy algorithm on the area of the territory that needs to be covered by the connection are given.

Transit Station Area Development and Demographic Outcomes

Transit Station Area Development and Demographic Outcomes

Detection Approach for Station Area Topology Change Based on Multi-Time Scale

Detection Approach for Station Area Topology Change Based on Multi-Time Scale

Optimization study of stochastic process and probabilistic model for line loss management efficiency in low-voltage station areas

Optimization study of stochastic process and probabilistic model for line loss management efficiency in low-voltage station areas

Impacts of pandemic service adaptations on job accessibility: A case study of the Bay Area Rapid Transit

The COVID-19 pandemic highlighted transit's crucial role as a social service, ensuring access to essential destinations. Despite this, unprecedented ridership lows forced agencies to implement service cuts, disproportionately affecting essential workers and vulnerable populations. However, the full extent of these impacts remains underexplored. While existing literature examines transit agency responses during the pandemic, much of the focus has been on public health and safety measures, overlooking the specifics of service adjustment strategies implemented. This study contributes to our understanding of transit agency pandemic responses throughout the pre-, peak-, and post-pandemic phases by 1) characterizing patterns in transit service adjustments and 2) extending pandemic accessibility literature by examining job-specific impacts. The framework integrates time series clustering, qualitative review of agency press releases, and transit accessibility analysis, using only publicly available data. Through a case study of Bay Area Rapid Transit, we find distinct clusters of stations characterized by patterns in weekday morning peak service restoration and station area demographics. While impacts to accessibility varied by time of day, the relative ordering of accessibility levels across income and race/ethnicity remained consistent throughout the pandemic. These findings contribute to our understanding of service adaptation impacts and inform equitable response strategies for future service planning and disruptions.