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Train Performance Analysis Using Heterogeneous Statistical Models
by
Yu, Jun
, Wang, Jianfeng
in
Arrival delay
/ Climate effects
/ Climate models
/ Heterogeneous Markov chain model
/ High speed rail
/ Likelihood ratio test
/ Markov analysis
/ Markov chains
/ matematisk statistik
/ Mathematical models
/ Mathematical Statistics
/ Passenger trains
/ Precipitation
/ Primary delay
/ Probability
/ Rain
/ Snow
/ Snow accumulation
/ Snow depth
/ Statistical analysis
/ Statistical models
/ Stratied Cox model
/ stratified Cox model
/ Survival analysis
/ Temperature
/ Variables
/ Wind
/ Winter climates
2021
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Train Performance Analysis Using Heterogeneous Statistical Models
by
Yu, Jun
, Wang, Jianfeng
in
Arrival delay
/ Climate effects
/ Climate models
/ Heterogeneous Markov chain model
/ High speed rail
/ Likelihood ratio test
/ Markov analysis
/ Markov chains
/ matematisk statistik
/ Mathematical models
/ Mathematical Statistics
/ Passenger trains
/ Precipitation
/ Primary delay
/ Probability
/ Rain
/ Snow
/ Snow accumulation
/ Snow depth
/ Statistical analysis
/ Statistical models
/ Stratied Cox model
/ stratified Cox model
/ Survival analysis
/ Temperature
/ Variables
/ Wind
/ Winter climates
2021
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Do you wish to request the book?
Train Performance Analysis Using Heterogeneous Statistical Models
by
Yu, Jun
, Wang, Jianfeng
in
Arrival delay
/ Climate effects
/ Climate models
/ Heterogeneous Markov chain model
/ High speed rail
/ Likelihood ratio test
/ Markov analysis
/ Markov chains
/ matematisk statistik
/ Mathematical models
/ Mathematical Statistics
/ Passenger trains
/ Precipitation
/ Primary delay
/ Probability
/ Rain
/ Snow
/ Snow accumulation
/ Snow depth
/ Statistical analysis
/ Statistical models
/ Stratied Cox model
/ stratified Cox model
/ Survival analysis
/ Temperature
/ Variables
/ Wind
/ Winter climates
2021
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Train Performance Analysis Using Heterogeneous Statistical Models
Journal Article
Train Performance Analysis Using Heterogeneous Statistical Models
2021
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Overview
This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance.
Publisher
MDPI AG
Subject
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