A novel approach to uncertainty analysis using methods of hybrid dimension reduction and improved maximum entropy

2019 ◽  
Vol 60 (5) ◽  
pp. 1841-1866 ◽  
Author(s):  
Zhiying Chen ◽  
Ping Zhou ◽  
Yong Liu ◽  
Pengfei Ji
Keyword(s):  
Uncertainty Analysis ◽  
Dimension Reduction ◽  
Maximum Entropy ◽  
Novel Approach

A new stochastic analysis method for mechanical components

2012 ◽  
Vol 227 (8) ◽  
pp. 1818-1829 ◽  
Author(s):  
YL Zhang ◽  
YM Zhang
Keyword(s):  
Finite Element ◽  
Dimension Reduction ◽  
Probability Density ◽  
Maximum Entropy ◽  
Maximum Entropy Principle ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Entropy Principle ◽  
Input Variables ◽  
First Four Moments

Univariate dimension-reduction integration, maximum entropy principle, and finite element method are employed to present a computational procedure for estimating probability densities and distributions of stochastic responses of structures. The proposed procedure can be described as follows: 1. Choose input variables and corresponding distributions. 2. Calculate the integration points and perform finite element analysis. 3. Calculate the first four moments of structural responses by univariate dimension-reduction integration. 4. Estimate probability density function and cumulative distribution function of responses by maximum entropy principle. Numerical integration formulas are obtained for non-normal distributions. The non-normal input variables need not to be transformed into equivalent normal ones. Three numerical examples involving explicit performance functions and solid mechanic problems without explicit performance functions are used to illustrate the proposed procedure. Accuracy and efficiency of the proposed procedure are demonstrated by comparisons of the estimated probability density functions and cumulative distribution functions obtained by maximum entropy principle and Monte Carlo simulation.

scholarly journals Morphologically-conditioned tonotactics in multilevel Maximum Entropy grammar

2016 ◽  
Vol 3 ◽  
Author(s):  
Stephanie S Shih ◽  
Sharon Inkelas
Keyword(s):  
Maximum Entropy ◽  
Harmonic Grammar ◽  
Common Base ◽  
Novel Approach ◽  
Indexed Constraints

This paper presents a novel approach to probabilistic morphologically-conditioned tonotactics, featuring a case study of Mende, in which tonotactics vary by lexical category. This variation in surface tone patterns is modeled via indexed weight adjustments (i.e., varying slopes) for each constraint in a Maximum Entropy Harmonic Grammar, quantifying the degree to which each lexical class follows basic tonotactic principles in a common base grammar. Approaching morphologically-conditioned phonotactics as indexed weight adjustments of a base grammar offers a solution to the existing stalemate between single grammar (e.g., indexed constraints) and multiple grammar (e.g., Stratal OT; cophonologies) models of lexically-sensitive phonological patterns.

Feature unionization: A novel approach for dimension reduction

2017 ◽  
Vol 52 ◽  
pp. 1253-1261 ◽  
Author(s):  
Abbas Jalilvand ◽  
Naomie Salim
Keyword(s):  
Dimension Reduction ◽  
Novel Approach
Sign in / Sign up

Export Citation Format

Share Document