Dependence modelling with regular vine copula models: a case-study for car crash simulation data

2015 ◽  
Vol 65 (3) ◽  
pp. 415-429 ◽  
Author(s):  
Ulf Schepsmeier ◽  
Claudia Czado
Keyword(s):  
Simulation Data ◽  
Crash Simulation ◽  
Copula Models ◽  
Car Crash ◽  
Dependence Modelling ◽  
Vine Copula

scholarly journals TOWARDS A FRAMEWORK FOR INTEGRATED AND COLLABORATIVE KNOWLEDGE MANAGEMENT FOR ENGINEERING DESIGN – A CASE STUDY

2020 ◽  
Vol 1 ◽  
pp. 559-568
Author(s):  
N. Fatfouta ◽  
J. Stal-Le Cardinal
Keyword(s):  
Knowledge Management ◽  
Design Process ◽  
Simulation Analysis ◽  
Management Approach ◽  
Crash Simulation ◽  
Car Crash ◽  
Collaborative Knowledge Management ◽  
Knowledge Intensive ◽  
Time Required

AbstractIn automotive industry, the design process is costly and time-consuming. Car safety is a crucial factor in the development of a vehicle, which is why crash simulation is an essential step in the design process. To improve car crash simulation analysis, it is necessary to reduce the time required and support the resolution of encountered design issues. We propose a knowledge management approach to support car crash simulation analysis and ensure the collaboration of different stakeholders. In a knowledge-intensive context, we used an ontology-based approach to formalise and capture knowledge.

scholarly journals Analysis of Car Crash Simulation Data with Nonlinear Machine Learning Methods

2013 ◽  
Vol 18 ◽  
pp. 621-630 ◽  
Author(s):  
Bastian Bohn ◽  
Jochen Garcke ◽  
Rodrigo Iza-Teran ◽  
Alexander Paprotny ◽  
Benjamin Peherstorfer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Simulation Data ◽  
Learning Methods ◽  
Crash Simulation ◽  
Machine Learning Methods ◽  
Car Crash

scholarly journals Empirical Study of Car Crash Simulation Analysis within the Development Phase

2019 ◽  
Vol 1 (1) ◽  
pp. 2843-2852 ◽  
Author(s):  
Naouress Fatfouta ◽  
Julie Stal-Le Cardinal ◽  
Christine Royer
Keyword(s):  
Empirical Study ◽  
Qualitative Analysis ◽  
Simulation Analysis ◽  
Development Phase ◽  
Vehicle Model ◽  
Crash Simulation ◽  
Automotive Company ◽  
Car Crash ◽  
Industrial Context ◽  
Current Practices

AbstractCar crash simulation analysis is an important phase within the vehicle development. It intends to analyse the crashworthiness of the vehicle model and examine the level of passive security. However, this activity is not trivial because of the considerable collaboration within the project, the large amount of analysed and exchanged data and a high exigency. Consequently, a solution to assist, ease and reduce the time of the process is desired.To study the current practices followed in the car crash simulation analysis an empirical study has been conducted. This study has been applied within the simulation analysis team, in the development phase, within an automotive company. This paper describes a qualitative analysis of the industrial context and diagnoses the dysfunctions in the current practices. This paper also highlights the current challenges encountered in the car crash simulation analysis.

scholarly journals Stochastic Modeling of Hydroclimatic Processes Using Vine Copulas

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2156
Author(s):  
George Pouliasis ◽  
Gina Alexandra Torres-Alves ◽  
Oswaldo Morales-Napoles
Keyword(s):  
Time Series ◽  
Stochastic Modeling ◽  
Copula Models ◽  
Multiple Processes ◽  
Spatial Dependencies ◽  
Probabilistic Dependence ◽  
Temporal And Spatial ◽  
Vine Copula ◽  
Synthetic Time Series ◽  
Hydroclimatic Variables

The generation of synthetic time series is important in contemporary water sciences for their wide applicability and ability to model environmental uncertainty. Hydroclimatic variables often exhibit highly skewed distributions, intermittency (that is, alternating dry and wet intervals), and spatial and temporal dependencies that pose a particular challenge to their study. Vine copula models offer an appealing approach to generate synthetic time series because of their ability to preserve any marginal distribution while modeling a variety of probabilistic dependence structures. In this work, we focus on the stochastic modeling of hydroclimatic processes using vine copula models. We provide an approach to model intermittency by coupling Markov chains with vine copula models. Our approach preserves first-order auto- and cross-dependencies (correlation). Moreover, we present a novel framework that is able to model multiple processes simultaneously. This method is based on the coupling of temporal and spatial dependence models through repetitive sampling. The result is a parsimonious and flexible method that can adequately account for temporal and spatial dependencies. Our method is illustrated within the context of a recent reliability assessment of a historical hydraulic structure in central Mexico. Our results show that by ignoring important characteristics of probabilistic dependence that are well captured by our approach, the reliability of the structure could be severely underestimated.

Estimating standard errors in regular vine copula models

2013 ◽  
Vol 28 (6) ◽  
pp. 2679-2707 ◽  
Author(s):  
Jakob Stöber ◽  
Ulf Schepsmeier
Keyword(s):  
Standard Errors ◽  
Copula Models ◽  
Vine Copula

scholarly journals Conservation Choices in the Face of Sea-Level Rise: A Case Study on Marsh Migration from Phippsburg, Maine

2017 ◽  
Vol 46 (2) ◽  
pp. 388-419 ◽  
Author(s):  
Sahan T. M. Dissanayake ◽  
Meagan K. Hennessey
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Land Conservation ◽  
Simulation Data ◽  
Sea Levels ◽  
Decision Method ◽  
The Face ◽  
Rising Sea Levels ◽  
Knapsack Algorithm

We analyze the benefits of incorporating climate change into land conservation decisions using wetland migration under rising sea-levels as a case study. We use a simple and inexpensive decision method, a knapsack algorithm implemented in Excel, with (1) simulation data to show that ignoring sea-level rise predictions lead to suboptimal outcomes, and (2) an application to land conservation in Phippsburg, Maine to show the real-world applicability. The simulation shows an 11-percent to almost 30-percent gain in increased benefits when accounting for sea-level rise. The results highlight that it is possible to, and important to, incorporate sea-level rise into conservation planning.

Sign in / Sign up

Export Citation Format

Share Document