scholarly journals Airline Schedule Buffers and Flight Delays: A Discrete Model

2020 ◽  
Author(s):  
Achim I. Czerny ◽  
Alberto A. Gaggero ◽  
Jan K. Brueckner
Keyword(s):  
Discrete Model ◽  
Flight Delays ◽  
Airline Schedule

scholarly journals Airline schedule buffers and flight delays: A discrete model

2021 ◽  
Vol 26-27 ◽  
pp. 100218
Author(s):  
Jan K. Brueckner ◽  
Achim I. Czerny ◽  
Alberto A. Gaggero
Keyword(s):  
Discrete Model ◽  
Flight Delays ◽  
Airline Schedule

scholarly journals Airline Schedule Disruption Management. The impact of flight delays on connection loss

2017 ◽  
Vol 105 ◽  
pp. 00013
Author(s):  
Hicham Rahil ◽  
Badr Abou El Majd ◽  
Mohammed Bouchoum
Keyword(s):  
Disruption Management ◽  
Flight Delays ◽  
The Impact ◽  
Airline Schedule

Airline Schedule Planning - Grundlagen und aktuelle Entwicklungen

2010 ◽  
Vol 39 (5) ◽  
pp. 230-235
Author(s):  
Jochen Gönsch
Keyword(s):  
Aktuelle Entwicklungen ◽  
Airline Schedule

scholarly journals Modeling and Analysis on Teacher-Student Relationship

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Li Xu ◽  
Qi Yang
Keyword(s):  
Discrete Model ◽  
Equation Model ◽  
Reciprocal Relations ◽  
Modeling And Analysis ◽  
Teacher Student ◽  
Teacher Student Relationship ◽  
Sample Data ◽  
Teachers And Students ◽  
Student Relationship ◽  
The Relationship

Although the teacher-student relationship has been addressed in some studies, the cooperation or reciprocal relations between teachers and students have not been explored sufficiently. In this paper, a difference equation model is applied to express the relationship, stability analysis at the positive steady state of the discrete model is done to verify that the performance output is not empty, and hypothesis testing is conducted to show the validity of the model by means of sample data from a college. Then some reasonable suggestions are proposed to improve the performance output of teachers and students.

scholarly journals Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 152
Author(s):  
Micha Zoutendijk ◽  
Mihaela Mitici
Keyword(s):  
Assignment Problem ◽  
Absolute Error ◽  
Aviation Industry ◽  
Probabilistic Forecasting ◽  
Flight Delays ◽  
Mixture Density ◽  
Assignment Model ◽  
Gate Assignment ◽  
Flight Delay ◽  
Delay Prediction

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting algorithms, Mixture Density Networks and Random Forest regression, are applied to predict flight delays at a European airport. The algorithms estimate well the distribution of arrival and departure flight delays with a Mean Absolute Error of less than 15 min. To illustrate the utility of the estimated delay distributions, we integrate these probabilistic predictions into a probabilistic flight-to-gate assignment problem. The objective of this problem is to increase the robustness of flight-to-gate assignments. Considering probabilistic delay predictions, our proposed flight-to-gate assignment model reduces the number of conflicted aircraft by up to 74% when compared to a deterministic flight-to-gate assignment model. In general, the results illustrate the utility of considering probabilistic forecasting for robust airport operations’ optimization.

Development and experimental realization of an adaptive neural-based discrete model predictive direct torque and flux controller for induction motor drive

2021 ◽  
Vol 108 ◽  
pp. 107418
Author(s):  
Abhimanyu Sahu ◽  
Kanungo Barada Mohanty ◽  
Rabi Narayan Mishra
Keyword(s):  
Induction Motor ◽  
Discrete Model ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Experimental Realization

scholarly journals Doing Good Better: Impure Altruism in Green Apparel Advertising

2019 ◽  
Vol 11 (20) ◽  
pp. 5762 ◽  
Author(s):  
So Young Song ◽  
Youn-Kyung Kim
Keyword(s):  
Data Analysis ◽  
Product Quality ◽  
Discrete Model ◽  
Online Survey ◽  
Marketing Strategies ◽  
Theoretical Development ◽  
Sustainable Lifestyle ◽  
Impure Altruism ◽  
Sustainable Behavior ◽  
Communal Harmony

In this study, we identify impure altruism as a duality of altruistic and egoistic warmth. We examine how these feelings motivate consumers to buy green apparel in response to advertisements. We test the effectiveness of the message orientation and its interactivity with a beneficiary and propose modeling impure altruism as the reason why consumers purchase green apparel. The study uses a quasi-experiment to estimate a comparison effect among advertising stimuli. We conduct an online survey among US consumers that garnered 586 responses for the main data analysis. The results indicate that egocentric appeals increase perceived uniqueness and that human beneficiary appeals lead to higher communal harmony. The findings show that communal harmony and global wellbeing prompt altruistic warmth and that uniqueness and product quality encourage egoistic warmth. Notably, altruistic warmth contributes to egoistic warmth, which indicates the existence of impurely altruistic consumers. Both altruistic and egoistic warmth lead to the intention of purchasing green apparel. We recommend “feel-good” marketing strategies to publicize the benefits of a sustainable lifestyle. The study contributes to the theoretical development of sustainability and can serve as an extension of a discrete model of altruism and egoism on consumers’ sustainable behavior.

scholarly journals Spatiotemporal Patterns Formed by a Discrete Nutrient-Phytoplankton Model with Time Delay

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Feifan Zhang ◽  
Wenjiao Zhou ◽  
Lei Yao ◽  
Xuanwen Wu ◽  
Huayong Zhang
Keyword(s):  
Steady State ◽  
Time Delay ◽  
Numerical Simulations ◽  
Functional Response ◽  
Bifurcation Analysis ◽  
Discrete Model ◽  
Continuous Model ◽  
Spatiotemporal Patterns ◽  
Homogeneous Steady State ◽  
Simulation Results

In this research, a continuous nutrient-phytoplankton model with time delay and Michaelis–Menten functional response is discretized to a spatiotemporal discrete model. Around the homogeneous steady state of the discrete model, Neimark–Sacker bifurcation and Turing bifurcation analysis are investigated. Based on the bifurcation analysis, numerical simulations are carried out on the formation of spatiotemporal patterns. Simulation results show that the diffusion of phytoplankton and nutrients can induce the formation of Turing-like patterns, while time delay can also induce the formation of cloud-like pattern by Neimark–Sacker bifurcation. Compared with the results generated by the continuous model, more types of patterns are obtained and are compared with real observed patterns.

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