Sensitivity Analysis the Ticket Price of Hangzhou to Shaoxing Intercity Line Based on the Equilibrium Model

2014 ◽  
Vol 587-589 ◽  
pp. 2160-2165
Author(s):  
Hui Peng ◽  
Wei Wei
Keyword(s):  
Sensitivity Analysis ◽  
Influence Factors ◽  
Operation Time ◽  
Rail Transit ◽  
Analysis Model ◽  
Ticket Price ◽  
Passenger Flow ◽  
Sensitivity Analysis Method ◽  
Ticket Prices ◽  
Intercity Rail Transit

Intercity rail transit's ticket prices as the key sensitive factors affect passenger flow, which is related to the accuracy of the prediction.This paper provides a model based on equilibrium price sensitivity analysis method. In order to make clear the relationship between the intercity rail transit ticket price and passenger flow, analysing the average operation time, cost and other influence factors, establishing the utility function to calculate the utility value, according to the equilibrium flow model of passenger flow, we can get the passenger flow of all kinds of transportation under the equilibrium traffic, on this basis, the sensitivity analysis model is used to get the connection between the traffic and the travel ticket in different modes of transport, In the end ,taking Hang-Shao intercity rail transit for example to analysis the sensitivity of the price. The research results show that the model and the algorithm has the higher reliability.

scholarly journals Prediction of Daily Entrance and Exit Passenger Flow of Rail Transit Stations by Deep Learning Method

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Huaizhong Zhu ◽  
Xiaoguang Yang ◽  
Yizhe Wang
Keyword(s):  
Deep Learning ◽  
Public Transportation ◽  
Influence Factors ◽  
Activation Function ◽  
Atmospheric Temperature ◽  
Weather Data ◽  
Rail Transit ◽  
Learning Method ◽  
Passenger Flow ◽  
Elevated Road

The prediction of entrance and exit passenger flow of rail transit stations is one of key research focuses in the area of intelligent transportation. Based on the big data of rail transit IC card (Public Transportation Card), this paper analyzes the data of major dynamic factors having effect on entrance passenger flow and exit passenger flow of rail transit stations: weather data, atmospheric temperature data, holiday and festival data, ground index data, and elevated road data and calculates the daily entrance passenger flow and daily exit passenger flow of individual rail transit stations with data reduction. Furthermore, based on the history data of passenger flow of rail transit stations and relevant influence factors, it applies the deep learning method to choose the relatively optimal hidden layer node by means of the cut-and-try method, set up input data and labeled data, select the activation function and loss function, and use the Adam Gradient Descent Optimization Algorithm for iterative global convergence. The results verify that this method accurately predicts the daily entrance passenger flow and daily exit passenger flow of rail transit stations with the prediction error of less than 4.1%. Finally, the proposed model is compared with the linear regression model.

Simulation-based sensitivity analysis for non-ignorably missing data

2017 ◽  
Vol 28 (1) ◽  
pp. 289-308 ◽  
Author(s):  
Peng Yin ◽  
Jian Q Shi
Keyword(s):  
Sensitivity Analysis ◽  
Missing Data ◽  
Evaluation System ◽  
Meta Analysis ◽  
Likelihood Method ◽  
Analysis Model ◽  
Bias Analysis ◽  
Mechanism Model ◽  
Novel Approach ◽  
Sensitivity Analysis Method

Sensitivity analysis is popular in dealing with missing data problems particularly for non-ignorable missingness, where full-likelihood method cannot be adopted. It analyses how sensitively the conclusions (output) may depend on assumptions or parameters (input) about missing data, i.e. missing data mechanism. We call models with the problem of uncertainty sensitivity models. To make conventional sensitivity analysis more useful in practice we need to define some simple and interpretable statistical quantities to assess the sensitivity models and make evidence based analysis. We propose a novel approach in this paper on attempting to investigate the possibility of each missing data mechanism model assumption, by comparing the simulated datasets from various MNAR models with the observed data non-parametrically, using the K-nearest-neighbour distances. Some asymptotic theory has also been provided. A key step of this method is to plug in a plausibility evaluation system towards each sensitivity parameter, to select plausible values and reject unlikely values, instead of considering all proposed values of sensitivity parameters as in the conventional sensitivity analysis method. The method is generic and has been applied successfully to several specific models in this paper including meta-analysis model with publication bias, analysis of incomplete longitudinal data and mean estimation with non-ignorable missing data.

Sensitive Analysis of Factors Affecting Soil Slope Stability

2012 ◽  
Vol 170-173 ◽  
pp. 1072-1075
Author(s):  
Yong Chun Cheng ◽  
Ping Jiang
Keyword(s):  
Sensitivity Analysis ◽  
Slope Stability ◽  
Influence Factor ◽  
Influence Factors ◽  
Analysis Method ◽  
Factors Affecting ◽  
Safety Coefficient ◽  
Analysis Process ◽  
Sensitivity Analysis Method ◽  
Slope Design

In order to get better calculation parameters for slope stability analysis, as well as provide a better theoretical basis for slope design and reinforcement. In this paper, based on the single factor sensitivity analysis method, the finite difference strength reduction method was taken to calculate the slope safety coefficient when influence factors change. Sensitivity analysis process was explained through a numerical example, the calculation result shows that, influence factor sensitivity of slope stability is related to the value of influence factor.

Setting Conditions of Long and Short Routing Mode of Rail Transit

2014 ◽  
Vol 644-650 ◽  
pp. 6327-6330
Author(s):  
Chen Yue
Keyword(s):  
Sensitivity Analysis ◽  
Evaluation System ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail ◽  
Train Routing ◽  
The Evaluation System

This paper analyzes the setting conditions on long and short routing mode of urban rail transit both qualitatively and quantitatively. The extended routing and the nested routing are selected to establish the evaluation system of train routing operation effect. Based on the sensitivity analysis of passenger flow and comparison of the operation effects of the train routing above, a conclusion when it is necessary to set long and short routing mode is drew. The instance of Metro Line 3 of City B verificates the method above and it is found the advantage of setting long and short routing mode is smaller as the passenger flow becomes balanced.

Structure Sensitivity Analysis and Dynamic Performance Optimization of Marine Gearbox

2017 ◽  
Author(s):  
Tengjiao Lin ◽  
Daokun Xie ◽  
Ziran Tan ◽  
Bo Liu
Keyword(s):  
Sensitivity Analysis ◽  
Performance Optimization ◽  
Optimization Design ◽  
Dynamic Performance ◽  
Structure Sensitivity ◽  
Superposition Method ◽  
Structure Parameters ◽  
Analysis Model ◽  
Vibration Acceleration ◽  
Response Optimization

The aim of this paper is to investigate the influence of structure parameters on the vibration characteristics and improve the dynamic performance of marine gearbox. A finite element model was established to solve the dynamic response by using modal superposition method. Based on the theory of multi-objective optimization design, the structure sensitivity analysis model of marine gearbox was established, which takes the structure parameters of the housing as design variables. The modal and response sensitivity was obtained by using the optimal gradient method. According to the results of sensitivity analysis, a modal and response optimization model of marine gearbox was established. The objective was to avoid natural frequencies from the excitation frequencies and minimize the root mean square of vibration acceleration of the evaluating points on the surface of housing. Then the modal optimization and response optimization of gearbox were carried out by using zero-order and first-order optimization method. The results indicate that the dynamic optimization of the gearbox can be achieved. After optimization, the amplitude of vibration acceleration of the evaluating points on the housing surface has been reduced and the resonance of marine gearbox can be avoided.

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