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About 10,000 papers for “simulation validation”

Model Validation Simulation.

Rani Moran (3315630), Mehdi Keramati (350780), Raymond J. Dolan (7484555) · Figshare · 2021

<p>In the main text figures (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008552#pcbi.1008552.g005" target="_blank">Fig 5C and 5D</a>) we generated model predictions based on 15 synthetic data sets per subject. While this methods allows noise reduction in calculations of model predations it renders a comparison between empirical and simulated effects difficult because it does not allow an assessment of how likely empirical effects will be generated by the models. Thus, we examined in greater detail the distribution of model predictions when a single dataset is generated per participant. A) We simulated for each participant a single synthetic experimental session (novel trial sequences which were generated as in the actual experiment), based on his or her best fitting parameters from the full model. We then repeated the mixed effects model reported in the section “The Effects of the Preceding Bandit-Phase on Chosen Reward Settings” for these synthetic data (i.e., for 30 synthetic participants). Thus, we obtained synthetic fixed effects for High/Low/Unrelated trials (as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008552#pcbi.1008552.g005" target="_blank">Fig 5B</a>). This entire procedure was repeated 1,001 times. Left panels present scatter plots for each pair of fixed effects (blue circles) and the empirical fixed effects (black *). Right panels present distributions for corresponding synthetic effect-contrasts (blue; estimated using Matlab’s routine “ksdensity”) and the empirical contrast (black). The titles reports the proportion of simulations which generated a contrast that is at least as large as the empirical contrast. The full model tends to generate positive contrasts and the empirical results fall comfortably within the range of model-simulations. B) Same but for the “No self-reflection sub-model”. This model predicts contrasts that are distributed around 0, and the empirical contrasts (especially High vs. Low, Other vs. Low) are very unlikely to emerge from this sub-model.</p> <p>(TIF)</p>

Cited by 0Open access

Validation of simulation models

Muniza Rehman, Stig Andur Pedersen · Journal of Experimental & Theoretical Artificial Intelligence · 2012

In philosophy of science, the interest for computational models and simulations has increased heavily during the past decades. Different positions regarding the validity of models have emerged but the views have not succeeded in capturing the diversity of validation methods. The wide variety of models with regards to their purpose, character, field of application and time dimension inherently calls for a similar diversity in validation approaches. A classification of models in terms of the mentioned elements is presented and used to shed light on possible types of validation leading to a categorisation of validation methods. Through different examples it is shown that the methods of validation depend on a number of things as the context of the model, the mathematical nature, the data available and the representational power of the model. In philosophy of science many discussions of validation of models has been somewhat narrow-minded reducing the notion of validation to establishment of truth. This article puts forward the diversity in applications of simulation models that demands a corresponding diversity in the notion of validation.

Cited by 6

Simulation Validation Literature Review

Matthew C. Ledwith, Raymond R. Hill, L. Champagne et al. · 2024

Simulation model validation is crucial for the effective use of simulation models in the operational research decision support paradigm. Unfortunately, too many operational researchers have insufficient understanding of the fundamental concepts and components of simulation model validation-and do not know where to go to gain that understanding. This chapter provides that all important initial introduction to simulation model validation and provides a wealth of useful references for those wishing to pursue deeper study.

Cited by 0

Validation of simulation models

Damien Foures · theses.fr (ABES) · 2015

Ce travail de thèse s'est intéressé à la validité des modèles de simulation dans le cadre du développement des systèmes complexes et critiques. Une analyse de l'approche d'ingénierie système, et plus particulièrement de l'aspect modélisation et simulation, a permis de constater qu'il est impossible d'établir de façon directe la validité du modèle de simulation. De nombreux points sont à l'origine de cette impossibilité, comme une mauvaise formulation des objectifs de simulation, une incohérence implémentatoire, les limites du moteur de simulation, etc. La validité d'un modèle de simulation étant définie pour un objectif de simulation, il est apparu important de proposer une approche globale de la M&S, associant un ensemble d'outils capables de détecter des incohérences entre les objectifs de simulation et les modèles du système d'intérêt. Ces outils, à destination de l'utilisateur de la simulation, permettent l'amélioration du niveau de confiance dans le modèle de simulation et donc dans les résultats de simulation. Notre étude se base sur la théorie de la M&S telle que proposée par B.P. Zeigler. En considérant le concept de cadre expérimental qui y est introduit, nous avons pu proposer un cadre méthodologique capable d'exprimer les objectifs de simulation de manière claire. Ce cadre méthodologique nous permet d'étudier les problématiques d'application et d'accommodation de la M& S que nous regroupons sous la problématique de compatibilité. Ainsi, notre premier objectif a été de proposer une approche capable de mesurer l'incohérence entre les objectifs de simulation et le modèle du système. En s'appuyant sur les méthodes formelles et la théorie des automates, nous avons établi un ensemble de métriques capables de mesurer le degré de compatibilité dynamique entre cadre expérimental et modèle du système d'intérêt. Pour cela, nous étudions en premier lieu la compatibilité dynamique entre automates à interface en utilisant la décomposition en arbre. Montrant les limites d'une telle approche, nous sommes passé à l'étude de la compatibilité entre modèles DEVS en utilisant la génération de graphes de classe, autrement appelés graphes d'atteignabilité. Cette étude formelle de la compatibilité nous permet de proposer un ensemble de bonnes propriétés de la simulation. Nous proposons finalement une méthodologie qui permet de guider l'utilisateur de la simulation dans l'élaboration de métriques permettant de mesurer ce niveau de compatibilité. S'appuyant sur les concepts de l'ingénierie dirigée par les modèles, nous proposons un langage dédié à la simulation permettant de guider l'utilisateur de la simulation dans l'évaluation de la validité des modèles de simulation.

Cited by 5Open access

Model Validation and Simulation

Abrahamczyk, Lars, Schwarz, Jochen, Werner, Frank · Publication Server of Weimar Bauhaus-University (Weimar Bauhaus-University) · 2013

Cited by 0Open access

Traffic flow simulation validation

Ang, Yong Chuan · DR-NTU (Nanyang Technological University) · 2018

Transportation issues are a major concern among ordinary citizens, as majority of the population travels between places daily. Singapore being one of the highly dense countries in the world, have to cope with the travel demand of its population. This increasing need for transportation is one of the factors that motivates researchers to study more about the traffic to get a better understanding about the phenomenon. Traffic simulator is a method widely used to learn and evaluate potential solutions by replicating the environment and the vehicle's behaviours as it allows researchers to test complex behaviour and scenarios in a risk-free environment. This study focus is on evaluating whether the traffic flow generated by simulation framework of CityMoS, a microscopic agent-based traffic simulator is similar with the real traffic observed in Singapore, through calibrating the "numberofAgents" parameters in CityMoS which defines the number of agents in the simulation in an attempt to replicate and resemble the traffic condition in Singapore. Overall, by calibrating only the “numberofAgents” parameter in CityMoS, it is able to
\n resemble approximately 15% of the traffic condition in Singapore. There are still many areas which can be done to enhance it further which is not covered in the scope of this project. Finally, a discussion on the reasons affecting the matching percentage and the recommendation on how to improve CityMoS is given for future implementation.

Cited by 0

VALIDATION OF SIMULATION MODELS

Cor van Dijkum, Dorien DeTombe, Etzel van Kuijk · 1999

2SISWO Netherlands Universities Institute for Coordinationof Research in Social Sciences.Plantage Muidergracht 4,1018 TV Amsterdamtel: 31 20 5270600 / fax: 31 20 6229430©1999 No part of this book may be reproduced inany form by print, photoprint, microfilm orany other means without the prior writtenpermission from the publisher.

Cited by 26

Model Validation and Simulation

:None · Bauhaus-Universität Weimar · 2013

The Bauhaus Summer School series provides an international forum for an exchange of methods and skills related to the interaction between different disciplines of modern engineering science. The 2012 civil engineering course was held in August over two weeks at Bauhaus-Universität Weimar. The overall aim was the exchange of research and modern scientific approaches in the field of model validation and simulation between well-known experts acting as lecturers and active students. Besides these educational intentions the social and cultural component of the meeting has been in the focus. 48 graduate and doctoral students from 20 different countries and 22 lecturers from 12 countries attended this summer school. Among other aspects, this activity can be considered successful as it raised the sensitivity towards both the significance of research in civil engineering and the role of intercultural exchange. This volume summarizes and publishes some of the results: abstracts of key note papers presented by the experts and selected student research works. The overview reflects the quality of this summer school. Furthermore the individual contributions confirm that for active students this event has been a research forum and a special opportunity to learn from the experiences of the researchers in terms of methodology and strategies for research implementation in their current work.

Cited by 0Open access

Validation of simulation method.

Lei Song (30203), Ji Wang (137458), Shibo Wang (847482) et al. · Figshare · 2025

<div> Traditional Savonius wind rotor has simple structure and can operate in any wind direction. However, its aerodynamic efficiency is lower than other types. A novel S-shaped wind rotor with three blades is proposed in order to improve the aerodynamic performance. The blade of the rotor is composed of two opposing convex circular arcs and its shape likes an ‘S’. The flow characteristics of the rotor are studied and analyzed by computational fluid dynamics (CFD) numerical simulation method. The steady and transient performances are studied using SST k-ω model and sliding mesh method, and are compared with that of traditional Savonius rotors. The results show that the average static torque coefficient of the rotor is 0.291, which is higher than the 0.222 of the Savonius rotor. The static vibration amplitude of the rotor is 0.375, which is lower than 0.709 of the Savonius rotor. The maximum power coefficient of the rotor is 0.228, which is also higher than the 0.226 of the Savonius rotor. The dynamic vibration amplitude of the novel rotor is 0.183, which is lower than the 0.492 of the Savonius rotor. The flow field analyses show that structure of the S-shaped blades can smooth the flow field and reduce the blocking effect in the overlap area. The study indicates that the proposed navel rotor can not only overcome the problems of sharp change in the internal flow field of traditional Savonius rotors, but also provide better operating stability and higher wind energy utilization. </div>

Cited by 0Open access

Experimental Validation and Simulation

Shashank Satyanarayana, Daniele Borio, Gérard Lachapelle et al. · 2016

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Cited by 0

Validation of numerical simulation.

Hyun-Chul Kim (1693873), Wonhye Lee (2239267), Daniel S. Weisholtz (14253434) et al. · Figshare · 2023

&lt;div&gt;&lt;p&gt;The effects of transcranial focused ultrasound (FUS) stimulation of the primary somatosensory cortex and its thalamic projection (&lt;i&gt;i&lt;/i&gt;.&lt;i&gt;e&lt;/i&gt;., ventral posterolateral nucleus) on the generation of electroencephalographic (EEG) responses were evaluated in healthy human volunteers. Stimulation of the unilateral somatosensory circuits corresponding to the non-dominant hand generated EEG evoked potentials across all participants; however, not all perceived stimulation-mediated tactile sensations of the hand. These FUS-evoked EEG potentials (FEP) were observed from both brain hemispheres and shared similarities with somatosensory evoked potentials (SSEP) from median nerve stimulation. Use of a 0.5 ms pulse duration (PD) sonication given at 70% duty cycle, compared to the use of 1 and 2 ms PD, elicited more distinctive FEP peak features from the hemisphere ipsilateral to sonication. Although several participants reported hearing tones associated with FUS stimulation, the observed FEP were not likely to be confounded by the auditory sensation based on a separate measurement of auditory evoked potentials (AEP) to tonal stimulation (mimicking the same repetition frequency as the FUS stimulation). Off-line changes in resting-state functional connectivity (FC) associated with thalamic stimulation revealed that the FUS stimulation enhanced connectivity in a network of sensorimotor and sensory integration areas, which lasted for at least more than an hour. Clinical neurological evaluations, EEG, and neuroanatomical MRI did not reveal any adverse or unintended effects of sonication, attesting its safety. These results suggest that FUS stimulation may induce long-term neuroplasticity in humans, indicating its neurotherapeutic potential for various neurological and neuropsychiatric conditions.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access

Validation of GOCE simulation

Mueller, J., Oberndorfer, H., Technische Univ. Muenchen (Germany). Inst. fuer Astronomische und Physikalische Geodaesie et al. · OpenGrey (Institut de l'Information Scientifique et Technique) · 1999

Cited by 0