Robust ensemble of metamodels based on the hybrid error measure

2021 ◽  
Author(s):  
Shuai Huang ◽  
Wenwen Jin ◽  
Bo Wu ◽  
Xin Zhang ◽  
Aman Elmi ◽  
...  
Keyword(s):  
Error Measure ◽  
Ensemble Of Metamodels

scholarly journals JPEG Quality Transcoding Using Neural Networks Trained with a Perceptual Error Measure

1999 ◽  
Vol 11 (1) ◽  
pp. 267-296 ◽  
Author(s):  
John Lazzaro ◽  
John Wawrzynek
Keyword(s):  
Prototype System ◽  
Training Procedure ◽  
Human Visual Perception ◽  
Error Measure ◽  
Jpeg Image ◽  
Perceptual Error ◽  
Image File ◽  
Visual Artifacts ◽  
Error Metric ◽  
Coded Images

A JPEG Quality Transcoder (JQT) converts a JPEG image file that was encoded with low image quality to a larger JPEG image file with reduced visual artifacts, without access to the original uncompressed image. In this article, we describe technology for JQT design that takes a pattern recognition approach to the problem, using a database of images to train statistical models of the artifacts introduced through JPEG compression. In the training procedure for these models, we use a model of human visual perception as an error measure. Our current prototype system removes 32.2% of the artifacts introduced by moderate compression, as measured on an independent test database of linearly coded images using a perceptual error metric. This improvement results in an average PSNR reduction of 0.634 dB.

scholarly journals Evaluation of Modified Fish-Bone Model for Estimating Seismic Demands of Irregular MRF Structures

2018 ◽  
Author(s):  
Amin Haghighat ◽  
Ashkan Sharifi
Keyword(s):  
Ground Motions ◽  
Fish Bone ◽  
Seismic Demands ◽  
Error Measure ◽  
Ductility Demand ◽  
Earthquake Records ◽  
Moment Resisting Frame ◽  
Different Types ◽  
Story Drift ◽  
Moment Resisting

This paper evaluates the accuracy of the Modified Fish-Bone (MFB) model for estimating the maximum inter-story drift ratio of irregular moment resisting frame (MRF) structures. To make this model applicable to irregular MRF structures, some modifications are made to the MFB formula. In order to evaluate the accuracy of the MFB model, several irregular frames with different types of irregularities are considered when subjected to different ground motions with different intensities. A local and a global error measure are defined and they are calculated for different frame models subjected to different earthquake records. The effects of different irregularities, ductility demand and frame height on the accuracy of the MFB model are investigated. Based on the results obtained from this evaluation, two simple and effective approaches are suggested to improve the MFB models.

scholarly journals Predicting fatalities among shark attacks: comparison of classifiers

2019 ◽  
Vol 8 (4) ◽  
pp. 360 ◽  
Author(s):  
Lim Mei Shi ◽  
Aida Mustapha ◽  
Yana Mazwin Mohmad Hassim
Keyword(s):  
Support Vector Machines ◽  
Performance Measurement ◽  
Support Vector ◽  
Error Measure ◽  
Accuracy And Precision ◽  
Vector Machines ◽  
Shark Attacks ◽  
Probabilistic Error

<span lang="EN-US">This paper presents the comparisons of different classifiers on predicting Shark attack fatalities. In this study, we are comparing two classifiers which are Support vector machines(SVMs) and Bayes Point Machines(BPMs) on Shark attacks dataset. The comparison of the classifiers were based on the accuracy, recall, precision and F1-score as the performance measurement. The results obtained from this study showed that BPMs predicted the fatality of shack attack victim experiment with higher accuracy and precision than the SVMs because BPMs have “average” identifier which can minimize the probabilistic error measure. From this experiment, it is concluded that BPMs are more suitable in predicting fatality of shark attack victim as BPMs is an improvement of SVMs.</span>

scholarly journals A multi-threshold approach and a realistic error measure for vanishing point detection in natural landscapes

2019 ◽  
Vol 85 ◽  
pp. 713-726 ◽  
Author(s):  
Álvaro García-Faura ◽  
Fernando Fernández-Martínez ◽  
Ricardo Kleinlein ◽  
Rubén San-Segundo ◽  
Fernando Díaz-de-María
Keyword(s):  
Vanishing Point ◽  
Error Measure ◽  
Natural Landscapes ◽  
Vanishing Point Detection ◽  
Point Detection ◽  
Threshold Approach

scholarly journals Dynamic Assessment of Vibration of Tooth Modification Gearbox Using Grey Bootstrap Method

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hui-liang Wang ◽  
Xiao-zhong Deng ◽  
Ju-bo Li ◽  
Jian-jun Yang
Keyword(s):  
Systematic Error ◽  
Performance Optimization ◽  
Bootstrap Method ◽  
Dynamic Assessment ◽  
Grey System Theory ◽  
Small Sample ◽  
Error Measure ◽  
True Value ◽  
Dynamic Uncertainty ◽  
Tooth Modification

The correlation analysis between gear modification and vibration characteristics of transmission system was difficult to quantify; a novel small sample vibration of gearbox prediction method based on grey system theory and bootstrap theory was presented. The method characterized vibration base feature of tooth modification gearbox by developing dynamic uncertainty, estimated true value, and systematic error measure, and these parameters could indirectly dynamically evaluate the effect of tooth modification. The method can evaluate the vibration signal of gearbox with installation of no tooth modification gear and topological modification gear, respectively, considering that 100% reliability is the constraints condition and minimum average uncertainty is the target value. Computer simulation and experiment results showed that vibration amplitude of gearbox was decreased partly due to topological tooth modification, and each value of average dynamic uncertainty, mean true value, and systematic error measure was smaller than the no tooth modification value. The study provided an important guide for tooth modification, dynamic performance optimization.

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