A Shape Function-Based Updating Parameters Selection Method for Long-Span Bridges

2009 ◽  
Author(s):  
Gang Liu ◽  
Zongming Huang ◽  
Yimin Shao ◽  
Shangbin Weng
Keyword(s):  
Shape Function ◽  
Model Updating ◽  
Optimization Method ◽  
Selection Method ◽  
Shape Functions ◽  
Long Span Bridges ◽  
Long Span ◽  
Parameters Selection ◽  
Modal Updating ◽  
Selection Of

We present a new updating parameters (UPs) selection method to tackle the bottleneck created by having too many UPs and limited measured data in model updating processing. While the model updating is performed by parameter optimization, an ill-conditioned numerical problem may be encountered or the reliability of the result may be unacceptable if too many parameters are used. The selection of UPs thus becomes a key issue, especially for long-span bridges with finite element models that should be divided into at least hundreds of element numbers. A new method is introduced to reduce the number of UPs and retain their physical significance. In this method, original UPs are described by a few macro-parameters based on shape functions. The model subsequently is updated by a normal optimization algorithm, such as the first-order optimization method. Based on a bridge with a three-span continuous beam and a long-span tie-arch, the optimal effects are investigated, with or without a shape function and using different types of shape functions. The results indicate that the effect of the modal updating based on a shape function is more robust than without shape function and the effect of a linear shape function is better than that of a constant value shape function.

SVM Parameter Optimization based on Immune Memory Clone Strategy and Application in Bus Passenger Flow Counting

2012 ◽  
Vol 4 (4) ◽  
pp. 74-80
Author(s):  
Zhu Fang ◽  
Wei Junfang
Keyword(s):  
Optimization Method ◽  
Parameters Optimization ◽  
Immune Memory ◽  
Support Vector ◽  
Model Parameters ◽  
Passenger Flow ◽  
Parameters Selection ◽  
Svm Model ◽  
Peak Model ◽  
Selection Of

The performance of support vector mchine (SVM) depends on the selection of model parameters, however, the selection of SVM model parameters more depends on the empirical value. According to the above deficiency, this paper proposed a parameters optimization method of support vector machine based on immune memory clone strategy (IMC). This method can solve the multi-peak model parameters selection problem better which is introduced by n-folded cross-verification. Tests on standard datasets show that this method has higher precision and faster optimization speed compared with other four methods. Then the proposed method was applied to bus passenger flow counting. The experimental results show that the method reposed in this paper obtains higher classification accuracy.

Research on Parameters Optimization Algorithm in Support Vector Machine Based on Immune Memory Clone Strategy

2012 ◽  
Vol 241-244 ◽  
pp. 1618-1621
Author(s):  
Fang Zhu ◽  
Jun Fang Wei
Keyword(s):  
Support Vector Machine ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Immune Memory ◽  
Support Vector ◽  
Model Parameters ◽  
Standard Data ◽  
Parameters Selection ◽  
Optimum Model ◽  
Selection Of

The performance of support vector machine (SVM) depends on the selection of model parameters, however, the selection of SVM model parameters more depends on the empirical value. According to the above deficiency, this paper proposed a parameters optimization method of support vector machine based on immune memory clone strategy (IMC). This method can solve the multi-peak model parameters selection problem better which is introduced by n-folded cross-verification and automatic acquire the optimum model parameters. Proved by the simulation results on standard data, this method has higher precision and faster optimization speed. In a word, it can be used as an effective and feasible SVM parameters optimization method.

A HYBRID PSO-SA OPTIMIZING APPROACH FOR SVM MODELS IN CLASSIFICATION

2013 ◽  
Vol 06 (05) ◽  
pp. 1350036 ◽  
Author(s):  
HUIYAN JIANG ◽  
LINGBO ZOU
Keyword(s):  
Operating Characteristic ◽  
Fitness Function ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Identification Accuracy ◽  
Support Vector ◽  
Swarm Optimization ◽  
Receiver Operating Characteristic Curves ◽  
Parameters Selection ◽  
Selection Of

Support vector machine (SVM) is a widely used tool in the field of image processing and pattern recognition. However, the parameters selection of SVMs is a dilemma in disease identification and clinical diagnosis. This paper proposed an improved parameter optimization method based on traditional particle swarm optimization (PSO) algorithm by changing the fitness function in the traditional evolution process of SVMs. Then, this PSO method was combined with simulated annealing global searching algorithm to avoid local convergence that traditional PSO algorithms usually run into. And this method has achieved better results which reflected in the receiver-operating characteristic curves in medical images classification and has gained considerable identification accuracy in clinical disease detection.

scholarly journals A Quick Assessment and Optimization Method for a Flutter Aerodynamic Measure of a Typical Flat Box Girder

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Feng Wang ◽  
Chuan Xiong ◽  
Zijian Wang ◽  
Congmin Guo ◽  
Hua Bai ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Wind Tunnel ◽  
Energy Input ◽  
Test Procedure ◽  
Optimization Method ◽  
Box Girder ◽  
Wind Tunnel Tests ◽  
Long Span Bridges ◽  
Long Span ◽  
Quick Assessment

Flutter is one of the most serious wind-induced vibration phenomena for long-span bridges and may cause the collapse of a bridge (e.g., the Old Tacoma Bridge, 1940). The selection and optimization of flutter aerodynamic measures are difficult in wind tunnel tests. It usually takes a long time and consumes more experimental materials. This paper presents a quick assessment and design optimization method for the flutter stability of a typical flat box girder of the long-span bridges. Numerical analysis could provide a reference for wind tunnel tests and improve the efficiency of the test process. Based on the modal energy exchange in the flutter microvibration process, the global energy input and local energy input are analyzed to investigate the vibration suppression mechanism of a flat steel box girder with an upper central stabilizer. Based on the comparison between the experimental and numerical data, a quick assessment method for the optimization work is proposed. It is practical to predict the effects of flutter suppression measures by numerical analysis. Thus, a wind tunnel test procedure for flutter aerodynamic measures is proposed which could save time and experimental materials.

Analysis of Structural Parameters of Cable-Stayed Suspension Bridges

2010 ◽  
Vol 163-167 ◽  
pp. 2068-2076
Author(s):  
Jing Qiu ◽  
Rui Li Shen ◽  
Huai Guang Li ◽  
Xun Zhang
Keyword(s):  
Structural Parameters ◽  
Three Dimensional ◽  
Suspension Bridge ◽  
Suspension Bridges ◽  
Analysis Method ◽  
Long Distance ◽  
Long Span Bridges ◽  
Long Span ◽  
And Behavior ◽  
Selection Of

The cable-stayed suspension bridge is a novel composite structure with great overall stiffness and the capacity to span a long distance, which has been proposed for the design of some extra long-span bridges. To take further research on mechanical properties and behavior of this type of structure, the proposed preliminary design of a cable-stayed suspension bridge with a main span of 1800m is analyzed. The three-dimensional nonlinear analysis method is used to investigate systematically the influence of various principal structural parameters on the static and dynamic behavior of bridges. These parameters include the rise-span ratio, the suspension-to-span ratio, the constraint condition of the stiffened girder, the number of auxiliary piers at side spans, the layout of suspension cables, and the elastic modulus of suspension cables. Meanwhile, the selection of the rational values of these parameters is discussed.

A Novel Parameter Optimization Algorithm Based on Immune Memory Clone Strategy

2012 ◽  
Vol 4 (3) ◽  
pp. 102-108
Author(s):  
Zhu Fang ◽  
Wei Junfang
Keyword(s):  
Support Vector Machine ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Immune Memory ◽  
Support Vector ◽  
Model Parameters ◽  
Parameters Selection ◽  
Svm Model ◽  
Peak Model ◽  
Selection Of

The performance of support vector machine (SVM) depends on the selection of model parameters, however, the selection of SVM model parameters more depends on the empirical value. According to the deficiency, this paper proposes a parameters optimization method of support vector machine based on immune memory clone strategy (IMC). This method can solve the multi-peak model parameters selection problem better which is introduced by n-folded cross-verification. Tests on standard datasets show that this method has higher precision and faster optimization speed compared with other four methods. The proposed method was applied to bus passenger flow counting. The experimental results show that the method reposed in this paper obtains higher classification accuracy.

scholarly journals SVM Parameter Optimization Based on Immune Memory Clone Strategy and Application in Bus Passenger Flow Counting

2012 ◽  
Vol 6-7 ◽  
pp. 694-699
Author(s):  
Fang Zhu ◽  
Jun Fang Wei
Keyword(s):  
Support Vector Machine ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Immune Memory ◽  
Support Vector ◽  
Model Parameters ◽  
Passenger Flow ◽  
Parameters Selection ◽  
Svm Model ◽  
Selection Of

The performance of support vector machine (SVM) depends on the selection of model parameters, however, the selection of SVM model parameters more depends on the empirical value. According to the above deficiency, this paper proposed a parameters optimization method of support vector machine based on immune memory clone strategy (IMC). This method can solve the multi-peak model parameters selection problem better which is introduced by n-folded cross-verification. Tests on standard datasets show that this method has higher precision and faster optimization speed compared with other four methods. Then the proposed method was applied to bus passenger flow counting. The experimental results show that the method reposed in this paper obtains higher classification accuracy.

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