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When drugs are administered extravascularly, a comprehensive evaluation through noncompartmental analysis becomes imperative. This analytical approach considers various parameters that play a crucial role in understanding the pharmacokinetics of these drugs.
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Node, place, ridership, and time model for rail-transit stations: a case study.

Ahad Amini Pishro1, Qihong Yang2, Shiquan Zhang3

  • 1Civil Engineering Department, Sichuan University of Science and Engineering, Zigong, 643000, China.

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|September 28, 2022
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Transit-Oriented Development (TOD) planning requires considering network accessibility (node value) and station land use (place value). A new Node-Place-Ridership-Time (NPRT) model effectively evaluates rail-transit stations by integrating these factors.

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Area of Science:

  • Urban Planning and Transportation Science
  • Geographic Information Systems (GIS) and Spatial Analysis
  • Civil Engineering and Public Transit Systems

Background:

  • Transit-Oriented Development (TOD) is crucial for urban planners aiming to enhance public transport facilities.
  • Key TOD parameters include network accessibility (node value) and station-area land use (place value).
  • Coordinating these factors necessitates understanding ridership patterns during peak and off-peak hours.

Purpose of the Study:

  • To propose a novel Node-Place-Ridership-Time (NPRT) model for evaluating rail-transit stations.
  • To investigate the impact of node value and place value on transit ridership.
  • To classify stations based on integrated TOD parameters and temporal factors.

Main Methods:

  • Utilized Multiple Linear Regression (MLR) to analyze the relationship between node value, place value, and ridership.
  • Applied K-Means and Cube Methods for station classification based on NPRT model outputs.
  • Conducted a case study on Chengdu rail-transit stations.

Main Results:

  • The NPRT model demonstrated accurate evaluation capabilities for rail-transit stations.
  • Identified significant impacts of network accessibility and land use on ridership.
  • Provided a robust framework for classifying stations based on multiple TOD-related factors.

Conclusions:

  • The proposed NPRT model offers a more accurate approach to evaluating rail-transit stations compared to previous methods.
  • Integrating node value, place value, and temporal ridership data enhances TOD planning.
  • The findings support data-driven decision-making for optimizing urban public transport systems.