Control of plot edge bias in forest stand growth simulation models

1977 ◽  
Vol 7 (1) ◽  
pp. 100-105 ◽  
Author(s):  
G. L. Martin ◽  
A. R. Ek ◽  
R. A. Monserud
Keyword(s):  
Linear Expansion ◽  
Simulation Models ◽  
Expansion Method ◽  
Forest Tree ◽  
New Approach ◽  
Stand Growth ◽  
Plot Size ◽  
Image Translation ◽  
Translation Techniques ◽  
Tree Spatial Pattern

Techniques for reducing edge bias are discussed and a new approach, termed the linear expansion method, is presented. This method is applicable to a wide variety of plot shapes and sizes and is unbiased under very general assumptions about the forest tree spatial pattern. The accuracy and efficiency of the linear expansion method were compared with (i) no edge bias correction and (ii) corrections by plot image translation techniques for several forest stands and spatial patterns. Results indicated translation and the linear expansion method behaved equally well on square plots 0.08 ha in size. As the plot size diminished or its shape deviated from square, the linear expansion method provided greater accuracy and lower bias than translation techniques. The linear expansion method also provided useful accuracy on circular plots where translation was not feasible.

Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design

1997 ◽  
Author(s):  
Chinghsin Tu ◽  
Russell R. Barton
Keyword(s):  
Monte Carlo ◽  
Robust Design ◽  
Simulation Models ◽  
Experiment Design ◽  
Production Yield ◽  
Design Stage ◽  
Yield Estimation ◽  
Simulation Code ◽  
New Approach ◽  
A Priority

Abstract The need for yield estimation strategies in the design stage is a priority recognized by industry. Yield estimates can be employed to assess the manufacturability of a design, and allow for modification to produce a robust design. Therefore, low yield of products can be avoided and costs for manufacturing can be reduced. This paper presents an accurate and time-efficient yield estimation approach for use with simulation models. We use a metamodel-based method, which is time-efficient compared to crude Monte Carlo yield estimation using the original simulation code. The approach employs a boundary-focused experiment design, which overcomes the inaccuracy of yield estimates that can occur when using a metamodel method. The results of two examples demonstrate the effectiveness of this new approach.

Dealing with Multiple Models in System Dynamics

2014 ◽  
Vol 3 (4) ◽  
pp. 17-35 ◽  
Author(s):  
Willem L. Auping ◽  
Erik Pruyt ◽  
Jan H. Kwakkel
Keyword(s):  
System Dynamics ◽  
Simulation Models ◽  
Dynamics Simulation ◽  
Multiple Models ◽  
Top Down ◽  
Bottom Up ◽  
New Approach ◽  
Behavioural Patterns ◽  
Copper Availability

This paper introduces an approach to compare simulation runs from multiple System Dynamics simulation models. Three dynamic hypotheses regarding the uncertain evolutions of long-term copper availability are introduced and used to illustrate the new approach. They correspond to three different perspectives on the copper system (global top-down, global bottom-up, and regional top-down). Although each of these models allows to generate a wealth of behavioural patterns, the focus in this paper is on the differences in trajectories caused by different models for identical values of shared parameters and identical settings of other assumptions, not on differences in behavioural patterns caused by each of the models. Hence, differences in trajectories between the three models are identified, quantified, and classified based on a quantified measure of difference. For these models, small differences between the trajectories are only found in stable runs, while the alternative perspectives are largely responsible for medium to large differences. Hence, it is concluded that multiple dynamic hypotheses may have to be modelled when dealing with uncertain issues.

Fast Speed Expansion Technique for the Transient Analysis of Automotive Clutches

2004 ◽  
Author(s):  
Jiayin Li
Keyword(s):  
Large Scale ◽  
Expansion Method ◽  
Linear Interpolation ◽  
New Approach ◽  
Fast Speed ◽  
Transient Problem ◽  
Expansion Technique ◽  
Eigen Solutions ◽  
Modal Coordinates ◽  
Thermoelastic Contact Problem

The transient modal analysis method (TMA) has been used to solve the inhomogeneous (loaded) transient thermoelastic contact problem (ITTEC). In the TMA method, the solution of the inhomogeneous transient problem is expressed in modal coordinates, corresponding to eigenfunctions of the homogeneous (unloaded) problem. However, for the large-scale ITTEC problem, this method is found to be extremely time-consuming, because of the computation-intensive of the eigen-solutions. This paper describes a new approach to solve the large-scale ITTEC problem with a dramatic reduction in computational complexity. The method is referred to as fast speed expansion method (FSE). With the FSE method, full eigen-solutions are performed only at a limited number of sparsely located speeds. For speeds between these speeds, eigenvectors are solved by linear interpolation, while the eigenvalues are computed from Taylor series. The method is illustrated with application to an automotive clutches.

scholarly journals Deep Generative Adversarial Networks for Image-to-Image Translation: A Review

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1705
Author(s):  
Aziz Alotaibi
Keyword(s):  
Three Dimensional ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Future Research ◽  
Comprehensive Overview ◽  
Adversarial Networks ◽  
Current State ◽  
Image Translation ◽  
Translation Techniques ◽  
Future Research Directions

Many image processing, computer graphics, and computer vision problems can be treated as image-to-image translation tasks. Such translation entails learning to map one visual representation of a given input to another representation. Image-to-image translation with generative adversarial networks (GANs) has been intensively studied and applied to various tasks, such as multimodal image-to-image translation, super-resolution translation, object transfiguration-related translation, etc. However, image-to-image translation techniques suffer from some problems, such as mode collapse, instability, and a lack of diversity. This article provides a comprehensive overview of image-to-image translation based on GAN algorithms and its variants. It also discusses and analyzes current state-of-the-art image-to-image translation techniques that are based on multimodal and multidomain representations. Finally, open issues and future research directions utilizing reinforcement learning and three-dimensional (3D) modal translation are summarized and discussed.

A SMS normalization system integrating multiple grammatical resources

2012 ◽  
Vol 19 (1) ◽  
pp. 121-141 ◽  
Author(s):  
J. OLIVA ◽  
J. I. SERRANO ◽  
M. D. DEL CASTILLO ◽  
Á. IGESIAS
Keyword(s):  
Natural Language ◽  
Machine Translation ◽  
Spanish Language ◽  
New Approach ◽  
The World ◽  
Translation Techniques ◽  
Different Levels

AbstractSMS language presents special phenomena and important deviations from natural language. Every day, an impressive amount of chat messages, SMS messages, and e-mails are sent all over the world. This widespread use makes important the development of systems that normalize SMS language into natural language. However, typical machine translation approaches are difficult to adapt to SMS language because of many irregularities that are shown by this kind of language. This paper presents a new approach for SMS normalization that combines lexical and phonological translation techniques with disambiguation algorithms at two different levels: lexical and semantic. The method proposed does not depend on big annotated corpus, which is difficult to build and is applied in two different domains showing its easiness of adaptation across different languages and domains. The results obtained by the system outperform some of the existing methods of SMS normalization despite the fact that the Spanish language and the corpus created have some features that complicate the normalization task.

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