A Cloud Model Based Computational Intelligence Algorithm for Parameter Identification of Chaotic Systems

2011 ◽  
Author(s):  
Junfeng Chen ◽  
Tiejun Wu
Keyword(s):  
Parameter Identification ◽  
Computational Intelligence ◽  
Chaotic Systems ◽  
Cloud Model ◽  
Model Based ◽  
Intelligence Algorithm

scholarly journals Enhanced Computational Intelligence Algorithm for Coverage Optimization of 6G Non-Terrestrial Networks in 3D Space

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 70419-70429
Author(s):  
Mohamed Abdel-Basset ◽  
Laila Abdel-Fatah ◽  
Khalid A. Eldrandaly ◽  
Nabil M. Abdel-Aziz
Keyword(s):  
Computational Intelligence ◽  
Coverage Optimization ◽  
3D Space ◽  
Intelligence Algorithm ◽  
Terrestrial Networks

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.

Developing a cloud model based risk assessment methodology for tunnel-induced damage to existing pipelines

2014 ◽  
Vol 29 (2) ◽  
pp. 513-526 ◽  
Author(s):  
Limao Zhang ◽  
Xianguo Wu ◽  
Queqing Chen ◽  
Miroslaw J. Skibniewski ◽  
Jingbing Zhong
Keyword(s):  
Risk Assessment ◽  
Cloud Model ◽  
Assessment Methodology ◽  
Model Based ◽  
Risk Assessment Methodology

A Study on the Post-Evaluation of the Social Environment of the Cloud Model-Based Wind Power Project

2011 ◽  
Vol 71-78 ◽  
pp. 2341-2346 ◽  
Author(s):  
Dong Xiao Niu ◽  
Fang Fang ◽  
Ying Ying Li
Keyword(s):  
Wind Power ◽  
Social Environment ◽  
Evaluation System ◽  
Cloud Model ◽  
Analytic Hierarchy ◽  
Model Based ◽  
Post Evaluation ◽  
The Social ◽  
Index Evaluation ◽  
Power Project

This study is to construct a post-evaluation system for the social environment of the wind power project and make a comprehensive assessment by the introducing the cloud model-based analytic hierarchy process. The process manifests the weight and index evaluation in the form of cloud model, which takes account of both ambiguity and randomness, improves the comprehensiveness and accuracy of the results and provides application and arguments for the method through practical examples.

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