scholarly journals Random dynamic analysis of vertical train–bridge systems under small probability by surrogate model and subset simulation with splitting

2020 ◽  
Vol 28 (3) ◽  
pp. 305-315
Author(s):  
Huoyue Xiang ◽  
Ping Tang ◽  
Yuan Zhang ◽  
Yongle Li
Keyword(s):  
Main Idea ◽  
Simulation Method ◽  
Ensemble Method ◽  
Traffic Density ◽  
Direct Monte Carlo Simulation ◽  
Maintenance Period ◽  
Small Probability ◽  
Subset Simulation ◽  
Track Irregularity ◽  
The Ensemble Method

Abstract The response of the train–bridge system has an obvious random behavior. A high traffic density and a long maintenance period of a track will result in a substantial increase in the number of trains running on a bridge, and there is small likelihood that the maximum responses of the train and bridge happen in the total maintenance period of the track. Firstly, the coupling model of train–bridge systems is reviewed. Then, an ensemble method is presented, which can estimate the small probabilities of a dynamic system with stochastic excitations. The main idea of the ensemble method is to use the NARX (nonlinear autoregressive with exogenous input) model to replace the physical model and apply subset simulation with splitting to obtain the extreme distribution. Finally, the efficiency of the suggested method is compared with the direct Monte Carlo simulation method, and the probability exceedance of train responses under the vertical track irregularity is discussed. The results show that when the small probability of train responses under vertical track irregularity is estimated, the ensemble method can reduce both the calculation time of a single sample and the required number of samples.

Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods

2017 ◽  
Vol 25 (4) ◽  
pp. 413-434 ◽  
Author(s):  
Justin Grimmer ◽  
Solomon Messing ◽  
Sean J. Westwood
Keyword(s):  
Treatment Effects ◽  
Ensemble Methods ◽  
Ensemble Method ◽  
Superior Performance ◽  
Accurate Estimation ◽  
Randomized Experiments ◽  
Heterogeneous Treatment Effects ◽  
Data Set ◽  
Heterogeneous Effects ◽  
The Ensemble Method

Randomized experiments are increasingly used to study political phenomena because they can credibly estimate the average effect of a treatment on a population of interest. But political scientists are often interested in how effects vary across subpopulations—heterogeneous treatment effects—and how differences in the content of the treatment affects responses—the response to heterogeneous treatments. Several new methods have been introduced to estimate heterogeneous effects, but it is difficult to know if a method will perform well for a particular data set. Rather than using only one method, we show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects. Building on a large literature on ensemble methods, we show how the weighting of methods can contribute to accurate estimation of heterogeneous treatment effects and demonstrate how pooling models lead to superior performance to individual methods across diverse problems. We apply the ensemble method to two experiments, illuminating how the ensemble method for heterogeneous treatment effects facilitates exploratory analysis of treatment effects.

Acoustic Events Detection in Dissimilarity Measurement Space

2013 ◽  
Vol 333-335 ◽  
pp. 764-768
Author(s):  
Lin Bin Jia ◽  
Lin Li ◽  
Rong Nie
Keyword(s):  
Euclidean Distance ◽  
Ensemble Method ◽  
Feature Subset ◽  
Environmental Sounds ◽  
Detection Model ◽  
Svm Algorithm ◽  
Comparable Performance ◽  
The Ensemble Method ◽  
Events Detection ◽  
Ensemble Experiments

The paper considers the problem of detecting acoustic events in a robust manner. The dissimilarity measurement is used to measure the distance between acoustic samples. Then this distance is used as the replacement of the Euclidean distance to build the detection model with the SVM algorithm. All the well-known features are considered when we build model in a way of feature subset ensemble. Experiments are conducted to detect events under a variety of environmental sounds. The model demonstrates the robustness of the ensemble method with dissimilarity measurement. The detection model has shown to produce comparable performance as human listeners.

Research of service selection algorithm for net-centric simulation task community

2014 ◽  
Vol 05 (03) ◽  
pp. 1450006
Author(s):  
Liyang Sun ◽  
Jianning Lin ◽  
Zhenqi Ju ◽  
Shaojie Mao ◽  
Zhong Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Traditional Approach ◽  
Main Idea ◽  
Service Selection ◽  
Simulation Method ◽  
Global Constraints ◽  
Variation Method ◽  
Local Optimum ◽  
Selection Algorithm ◽  
Simulation Task

Being a new-generation C4ISR system simulation method, the construction approach of net-centric simulation (NCS) is developing toward net-centric from the traditional approach of platform-centric. NCS is mainly completed by the construction of the simulation task community (STC), the key to which being the dynamic integration of the various services spread in the network in order to form a new STC that meets the requirements of different users. In this study, a simulation task community service selection algorithm (STCSSA) is proposed. The main idea of this algorithm is to transform the construction of STC to the searching of optimal multi-objectives services with QoS global constraints. This paper first introduces the QoS model of STC and evaluates the service composition process, then presents the detailed operating process of STCSSA and design of the dynamic inertia weight strategy of the algorithm, and also proposes an optional variation method. Comparative tests were performed on STCSSA with other particle swarm optimization algorithms. It was validated from the perspective of performance that the proposed algorithm has advantages in improving the rate of convergence and avoiding local optimum, and from the perspective of practical application STCSSA also demonstrated feasibility in the construction of large-scale NCS task community.

Effect of Geometrical Uncertainty on Cemented Hip Implant Structural Integrity

2009 ◽  
Vol 131 (5) ◽  
Author(s):  
Mamadou T. Bah ◽  
Martin Browne
Keyword(s):  
Structural Integrity ◽  
Simulation Method ◽  
Cement Mantle ◽  
Direct Monte Carlo Simulation ◽  
Modes Of Failure ◽  
Surface Method ◽  
Element Input ◽  
Von Mises ◽  
Von Mises Stresses ◽  
Geometrical Uncertainty

A large number of parameters such as material properties, geometry, and structural strength are involved in the design and analysis of cemented hip implants. Uncertainties in these parameters have a potential to compromise the structural performance and lifetime of implants. Statistical analyses are well suited to investigating this type of problem as they can estimate the influence of these uncertainties on the incidence of failure. Recent investigations have focused on the effect of uncertainty in cement properties and loading condition on the integrity of the construct. The present study hypothesizes that geometrical uncertainties will play a role in cement mantle failure. Finite element input parameters were simulated as random variables and different modes of failure were investigated using a response surface method (RSM). The magnitude of random von Mises stresses varied up to 8 MPa, compared with a maximum nominal value of 2.38 MPa. Results obtained using RSM are shown to match well with a benchmark direct Monte Carlo simulation method. The resulting probability that the maximum cement stress will exceed the nominal stress is 62%. The load and the bone and prosthesis geometries were found to be the parameters most likely to influence the magnitude of the cement stresses and therefore to contribute most to the probability of failure.

An Investigation into Air Traffic Control by a Simulation Method

1951 ◽  
Vol 4 (1) ◽  
pp. 34-65
Author(s):  
R. B. Coulson ◽  
V. D. Burgmann
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Air Traffic Control ◽  
Simulation Method ◽  
Air Traffic ◽  
Traffic Density ◽  
Laboratory Equipment ◽  
System A ◽  
Full Scale Tests

It is now generally recognized that, under instrument conditions, traffic congestion at busy airports is already bad and any further increase in traffic density would be unmanageable without improvements in methods of air traffic control. A study of the problems of air traffic control by full-scale tests is prohibitively expensive and a practical alternative is required. This paper describes a series of investigations into air traffic control problems by simulation methods.Laboratory equipment suitable for such experiments is described briefly and has been shown to give a reliable quantitative assessment of the effect of changes in a control system. A number of possible control systems were studied in detail.

scholarly journals An ensemble method to predict target genes and pathways in uveal melanoma

2018 ◽  
Vol 13 (1) ◽  
pp. 90-96
Author(s):  
Chao Wei ◽  
Lei Wang ◽  
Han Zhang
Keyword(s):  
Uveal Melanoma ◽  
Target Genes ◽  
Pearson Correlation ◽  
Correlation Method ◽  
Enrichment Analysis ◽  
Ensemble Method ◽  
Borda Count ◽  
Pathway Enrichment Analysis ◽  
Mirna Targets ◽  
The Ensemble Method

AbstractObjectiveThis work proposes to predict target genes and pathways for uveal melanoma (UM) based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC), a causal inference method (IDA) and a regression method (Lasso) utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

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