Two different approaches for parameter identification in a spatial–temporal rumor propagation model based on Turing patterns

2021 ◽  
pp. 106174
Author(s):  
Linhe Zhu ◽  
Le He
Keyword(s):  
Parameter Identification ◽  
Propagation Model ◽  
Turing Patterns ◽  
Model Based ◽  
Rumor Propagation

A Rumor & Anti-rumor Propagation Model Based on Data Enhancement and Evolutionary Game

2020 ◽  
pp. 1-1
Author(s):  
Yunpeng Xiao ◽  
Wen Li ◽  
Shuai Qiang ◽  
Qian Li ◽  
Hanchun Xiao ◽  
...  
Keyword(s):  
Evolutionary Game ◽  
Propagation Model ◽  
Model Based ◽  
Rumor Propagation

scholarly journals Dynamic analysis of rumor propagation model based on true information spreader

2019 ◽  
Vol 68 (15) ◽  
pp. 150501
Author(s):  
Ju-Ping Zhang ◽  
Hao-Ming Guo ◽  
Wen-Jun Jing ◽  
Zhen Jin
Keyword(s):  
Dynamic Analysis ◽  
Propagation Model ◽  
Model Based ◽  
Rumor Propagation

mparison of model-based identification methods for reserve-capacity assessment of existing bridges

2018 ◽  
Author(s):  
Marco Proverbio ◽  
François-Xavier Favre ◽  
Ian F. C. Smith
Keyword(s):  
Parameter Identification ◽  
Structural Identification ◽  
Domain Model ◽  
Reserve Capacity ◽  
Steel Bridge ◽  
Model Based ◽  
Wrong Identification ◽  
Alternative Methodology ◽  
Existing Bridges ◽  
Residual Minimization

The goal of model-based structural identification is to find suitable values of parameters that affect structure behaviour. To this end, measurements are often compared with predictions of finiteelement models. Although residual minimization (RM) is a prominent methodology for structural identification, it provides wrong parameter identification when flawed model classes are adopted. Error-domain model falsification (EDMF) is an alternative methodology that helps identify candidate models – models that are compatible with behaviour measurements – among an initial model population. This study focuses on the comparison between RM and EDMF for the structural identification of a steel bridge in Exeter (UK). Advantages and limitations of both methodologies are discussed with reference to parameter identification and prognosis tasks such as quantification of reserve capacity. Results show that the employment of RM may lead to wrong identification and unsafe estimations of reserve capacity.

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