Simulation-Based Airport Capacity Estimation

2013 ◽  
Author(s):  
Krishnakumar Ramamoorthy ◽  
George Hunter
Keyword(s):  
Capacity Estimation ◽  
Airport Capacity ◽  
Simulation Based

A Categorical Model for Airport Capacity Estimation Using Hierarchical Clustering

2017 ◽  
Vol 4 (4) ◽  
pp. 245-273
Author(s):  
Gokcin Cinar ◽  
Hernando Jimenez ◽  
Dimitri N. Mavris
Keyword(s):  
Hierarchical Clustering ◽  
Capacity Estimation ◽  
Categorical Model ◽  
Airport Capacity

Studies of capacity estimation of the airport with two parallel runways

2005 ◽  
Vol 109 (1098) ◽  
pp. 395-401 ◽  
Author(s):  
Yihua Cao ◽  
Yong Chen ◽  
Yong Zhou
Keyword(s):  
Mathematical Model ◽  
Historical Data ◽  
Analytical Models ◽  
Capacity Estimation ◽  
Capacity Curves ◽  
Airport Capacity ◽  
The Mathematical Model

Abstract The analytical capacity models of an airport with two runways system are developed in this paper and the theoretical capacity curves yielded by this model are analysed. The statistic airport capacity estimation methodology based on historical data is introduced as well. Both analytical models and statistic strategy are applied to estimate the capacity of the two runways system of a typical airport. Two sets of airport capacity curves obtained in different ways are compared and analysed. The result of the analysis indicates that the mathematical model works effectively in a fairly accurate way in the estimation of airport capacity.

scholarly journals A Simulation Based Proactive Approach for Smart Capacity Estimation in the Context of Dynamic Positions and Events

2020 ◽  
Vol 5 (6) ◽  
pp. 423-438
Author(s):  
Naeem Ahmed Haq Nawaz ◽  
Hamid Raza Malik ◽  
Ahmed Jaber Alshaor ◽  
Kamran Abid
Keyword(s):  
Capacity Estimation ◽  
Proactive Approach ◽  
Simulation Based

Inquiry Learning

2009 ◽  
Vol 23 (2) ◽  
pp. 117-127 ◽  
Author(s):  
Astrid Wichmann ◽  
Detlev Leutner
Keyword(s):  
Scientific Reasoning ◽  
Inquiry Learning ◽  
Instructional Support ◽  
Test Results ◽  
Knowledge Test ◽  
Simulation Based ◽  
Scientific Experiments ◽  
Specific Support ◽  
Science Classes

Seventy-nine students from three science classes conducted simulation-based scientific experiments. They received one of three kinds of instructional support in order to encourage scientific reasoning during inquiry learning: (1) basic inquiry support, (2) advanced inquiry support including explanation prompts, or (3) advanced inquiry support including explanation prompts and regulation prompts. Knowledge test as well as application test results show that students with regulation prompts significantly outperformed students with explanation prompts (knowledge: d = 0.65; application: d = 0.80) and students with basic inquiry support only (knowledge: d = 0.57; application: d = 0.83). The results are in line with a theoretical focus on inquiry learning according to which students need specific support with respect to the regulation of scientific reasoning when developing explanations during experimentation activities.

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