scholarly journals A conservative scene model update policy

2012 ◽  
Author(s):  
Nick Mould ◽  
Joseph P. Havlicek
Keyword(s):  
Model Update

A Novel Approach to the Banyu Urip 3D Geologic Model Update

2018 ◽  
Author(s):  
Adam Zeiza
Keyword(s):  
Novel Approach ◽  
Model Update ◽  
Geologic Model

scholarly journals FedPSO: Federated Learning Using Particle Swarm Optimization to Reduce Communication Costs

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 600
Author(s):  
Sunghwan Park ◽  
Yeryoung Suh ◽  
Jaewoo Lee
Keyword(s):  
Particle Swarm Optimization ◽  
Data Privacy ◽  
Particle Swarm ◽  
Global Model ◽  
Network Communication ◽  
Improve Performance ◽  
Communication Performance ◽  
Swarm Optimization ◽  
Model Update ◽  
Network Environments

Federated learning is a learning method that collects only learned models on a server to ensure data privacy. This method does not collect data on the server but instead proceeds with data directly from distributed clients. Because federated learning clients often have limited communication bandwidth, communication between servers and clients should be optimized to improve performance. Federated learning clients often use Wi-Fi and have to communicate in unstable network environments. However, as existing federated learning aggregation algorithms transmit and receive a large amount of weights, accuracy is significantly reduced in unstable network environments. In this study, we propose the algorithm using particle swarm optimization algorithm instead of FedAvg, which updates the global model by collecting weights of learned models that were mainly used in federated learning. The algorithm is named as federated particle swarm optimization (FedPSO), and we increase its robustness in unstable network environments by transmitting score values rather than large weights. Thus, we propose a FedPSO, a global model update algorithm with improved network communication performance, by changing the form of the data that clients transmit to servers. This study showed that applying FedPSO significantly reduced the amount of data used in network communication and improved the accuracy of the global model by an average of 9.47%. Moreover, it showed an improvement in loss of accuracy by approximately 4% in experiments on an unstable network.

scholarly journals Finite Element Model Update via Bayesian Estimation and Minimization of Dynamic Residuals

AIAA Journal ◽  
1997 ◽  
Vol 35 (5) ◽  
pp. 879-886 ◽  
Author(s):  
Kenneth F. Alvin
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Bayesian Estimation ◽  
Element Model ◽  
Model Update ◽  
Dynamic Residuals

scholarly journals CAD model update on as-built geometries with morphing technique: ITER winding pack

2021 ◽  
Vol 1038 (1) ◽  
pp. 012082
Author(s):  
E Pompa ◽  
S Porziani ◽  
C Groth ◽  
A Chiappa ◽  
G D’Amico ◽  
...  
Keyword(s):  
Cad Model ◽  
Model Update

An Adaptive Model Update Object Tracking Algorithm based on DenseNet Features

2020 ◽  
Author(s):  
Sugang Ma ◽  
Lei Zhang ◽  
Lei Pu ◽  
Xiaobao Yang ◽  
Zhiqiang Hou
Keyword(s):  
Object Tracking ◽  
Tracking Algorithm ◽  
Adaptive Model ◽  
Model Update

Cooperative Federated Learning and Model Update Verification in Blockchain Empowered Digital Twin Edge Networks

2021 ◽  
pp. 1-1
Author(s):  
Li Jiang ◽  
Hao Zheng ◽  
Hui Tian ◽  
Shengli Xie ◽  
Yan Zhang
Keyword(s):  
Digital Twin ◽  
Model Update ◽  
Edge Networks

Investigation of a Model Update Technique for Flexible Multibody Simulation

2019 ◽  
pp. 247-254 ◽  
Author(s):  
Andreas Schulze ◽  
Johannes Luthe ◽  
János Zierath ◽  
Christoph Woernle
Keyword(s):  
Multibody Simulation ◽  
Model Update ◽  
Flexible Multibody

Detection of model-plant mismatch and model update for reaction systems using concept of extents

2018 ◽  
Vol 72 ◽  
pp. 17-29
Author(s):  
D.M. Darsha Kumar ◽  
Shankar Narasimhan ◽  
Nirav Bhatt
Keyword(s):  
Reaction Systems ◽  
Model Plant ◽  
Model Update

A Review of the PSA Model Truncation Convergence Issues at Some ENS Plants

2006 ◽  
Author(s):  
Fatma Yilmaz
Keyword(s):  
Safety Assessment ◽  
Recent Model ◽  
Probabilistic Safety Assessment ◽  
Rule Of Thumb ◽  
Model Update ◽  
The Subject ◽  
River Bend ◽  
Probabilistic Safety

This study provides the insights gained from the Probabilistic Safety Assessment (PSA) model update of several Entergy Nuclear South (ENS) plants with respect to truncation convergence based on the limited guidance on the issue in the industry. The industry rule of thumb, the ASME and NRC guidance and requirements on the subject have been reviewed. The recent model updates performed at some of the ENS plants (River Bend, ANO 1 and 2) considered these criteria. Based on the current criteria used in the industry for truncation convergence, the recent PSA model update results for the River Bend Station (RBS) and ANO-1 are not converging even at a low truncation limit of 1E−11/reactor-year (yr). Many improvements were introduced in the recent model updates and convergence was expected at higher truncation values. This paper discusses the issues identified that are related to the convergence of the PSA results at low truncation limits.

Interplanetary meteoroid environment model update

1998 ◽  
Author(s):  
Henry Garrett ◽  
S. Drouilhet ◽  
J. Oliver ◽  
R. Evans
Keyword(s):  
Environment Model ◽  
Model Update
Sign in / Sign up

Export Citation Format

Share Document