On the Independence of the Standardized One-Step-Ahead Prediction Errors in ARCH Models

2005 ◽  
Author(s):  
Stavros Antonios Degiannakis ◽  
Evdokia Xekalaki
Keyword(s):  
Prediction Errors ◽  
Arch Models ◽  
One Step

Method Evaluation for Short-Term Wind Speed Prediction Considering Multi Regions in Japan

2016 ◽  
Vol 28 (5) ◽  
pp. 681-686
Author(s):  
Ikki Tanaka ◽  
◽  
Hiromitsu Ohmori
Keyword(s):  
Wind Speed ◽  
Energy Use ◽  
Absolute Error ◽  
External Input ◽  
Support Vector ◽  
Prediction Errors ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
One Step ◽  
Text Prediction

[abstFig src='/00280005/09.jpg' width='300' text='Prediction errors at observation points' ] Wind energy use is being developed worldwide. Improving wind speed forecasting techniques has become important due to their economic impact on power system operation with increasing wind power penetration. Wind speed prediction is generally difficult due to wind’s intermittent nature, so many approaches have been proposed by researchers. The viability of these techniques has been verified, however, in only a certain few areas, rather than being evaluated quantitatively in many different locations. We use data from different parts of Japan for one-step-ahead prediction and applied different approaches at each point, which was then evaluated such as mean absolute error. We used the persistent model, the ARMA-GARCH model, the nonlinear autoregressive network with external input (NARX), the recurrent neural network (RNN), and support vector regression (SVR). Our results suggest that it is difficult to create the same model which minimizes error in all areas, confirming the need for individual predictors for individual regions.

scholarly journals A System-Based Approach to Monitoring the Performance of a Human Neuromusculoskeletal System

2020 ◽  
Vol 7 (2) ◽  
Author(s):  
Marcus Mussleman ◽  
Deanna H. Gates ◽  
Dragan Djurdjanovic
Keyword(s):  
Human Subjects ◽  
Prediction Errors ◽  
Joint Models ◽  
Frequency Distributions ◽  
Time Frequency ◽  
Angular Velocities ◽  
One Step ◽  
Electromyographic Signals ◽  
Instantaneous Energy ◽  
Over Time

This paper presents a system-based method for monitoring a human neuromusculoskeletal (NMS) system. It is based on autoregressive models with exogenous inputs, which link surface electromyographic signals and joint kinematic variables in order to detect changes in system dynamics, as well as to assess joint level and muscle level contributions to those changes. Instantaneous energy and mean frequency of time frequency distributions of electromyographic signals were used as model inputs, while angular velocities of the monitored joints served as outputs. Slow temporal changes in the behavior of the entire system or individual joint models were tracked by analyzing one-step ahead prediction errors of the corresponding models over time. Finally, analysis of the recursively updated models, which tracked the NMS dynamics over time, was used to characterize these changes at the joint and muscular levels. Themethodology is demonstrated on data recorded from 12 human subjects completing a repetitive sawing motion until voluntary exhaustion. Statistically significant decreasing trends in the similarities of the NMS models to those observed in the rested state were observed in all subjects. In addition, decreased joint response to muscle activity, as well as changes in the coordination and motion planning have been detected with all subjects, indicating their fatigue.

scholarly journals Extrapolation of AR models using cubic splines for damage progression evaluation in composite structures

2020 ◽  
pp. 1045389X2096317 ◽  
Author(s):  
Samuel da Silva ◽  
Jessé Paixão ◽  
Marc Rébillat ◽  
Nazih Mechbal
Keyword(s):  
Composite Structures ◽  
Lamb Waves ◽  
Ar Model ◽  
Composite Panel ◽  
Model Parameters ◽  
Prediction Errors ◽  
Sensors And Actuators ◽  
One Step ◽  
Auto Regressive ◽  
Ar Models

This paper presents the potentiality of the use of extrapolation of a set of Auto-Regressive (AR) models to inspect a future damage sensitive indices based on changes in one-step-ahead prediction errors. The key idea is to use multiple AR models to assess a data-driven model to represent and predict the time-series outputs of the PZT sensors receiving Lamb waves in a composite coupon. Based on some simplified assumptions, after detecting initial damage using some previous classifier, its progression evaluation by interpolating the AR parameters is proposed and examined based on cubic spline functions. After, an extrapolated AR model using this information may verify the future state and to inspect how the damage could progress. An aeronautical composite panel with bonded piezoelectric elements that act both as sensors and actuators is utilized to examine the relationship between the variation of the identified model parameters with various levels of simulated damage. The results have shown a smooth and adequate correlation between the estimates obtained by the extrapolated model and the actual progress of the damage observed. The significant advantage of the proposed procedure is implementing this task without adopting a complicated and costly mathematical-physical model.

Above and beyond the content: Feelings influence mental simulations

2020 ◽  
Vol 43 ◽  
Author(s):  
Kellen Mrkva ◽  
Luca Cian ◽  
Leaf Van Boven
Keyword(s):  
Mental Representation ◽  
Mental Simulation ◽  
Past Experience ◽  
Prediction Errors

Abstract Gilead et al. present a rich account of abstraction. Though the account describes several elements which influence mental representation, it is worth also delineating how feelings, such as fluency and emotion, influence mental simulation. Additionally, though past experience can sometimes make simulations more accurate and worthwhile (as Gilead et al. suggest), many systematic prediction errors persist despite substantial experience.

An Interactive Minicomputer Program for the Indexing and Simulation of Electron Diffraction Patterns

1976 ◽  
Vol 34 ◽  
pp. 542-543
Author(s):  
R.P. Goehner ◽  
W.T. Hatfield ◽  
Prakash Rao
Keyword(s):  
Electron Diffraction ◽  
Real Time ◽  
Pattern Analysis ◽  
Flow Diagram ◽  
Hard Copy ◽  
Time Analysis ◽  
Real Time Analysis ◽  
Transmission Electron ◽  
One Step ◽  
Diffraction Patterns

Computer programs are now available in various laboratories for the indexing and simulation of transmission electron diffraction patterns. Although these programs address themselves to the solution of various aspects of the indexing and simulation process, the ultimate goal is to perform real time diffraction pattern analysis directly off of the imaging screen of the transmission electron microscope. The program to be described in this paper represents one step prior to real time analysis. It involves the combination of two programs, described in an earlier paper(l), into a single program for use on an interactive basis with a minicomputer. In our case, the minicomputer is an INTERDATA 70 equipped with a Tektronix 4010-1 graphical display terminal and hard copy unit.A simplified flow diagram of the combined program, written in Fortran IV, is shown in Figure 1. It consists of two programs INDEX and TEDP which index and simulate electron diffraction patterns respectively. The user has the option of choosing either the indexing or simulating aspects of the combined program.

Nutrient-regulated gene expression in eukaryotes

2006 ◽  
Vol 73 ◽  
pp. 85-96 ◽  
Author(s):  
Richard J. Reece ◽  
Laila Beynon ◽  
Stacey Holden ◽  
Amanda D. Hughes ◽  
Karine Rébora ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Transcriptional Control ◽  
Direct Interaction ◽  
Signalling Pathways ◽  
A Cell ◽  
One Step ◽  
Higher Eukaryotes ◽  
Regulated Gene Expression

The recognition of changes in environmental conditions, and the ability to adapt to these changes, is essential for the viability of cells. There are numerous well characterized systems by which the presence or absence of an individual metabolite may be recognized by a cell. However, the recognition of a metabolite is just one step in a process that often results in changes in the expression of whole sets of genes required to respond to that metabolite. In higher eukaryotes, the signalling pathway between metabolite recognition and transcriptional control can be complex. Recent evidence from the relatively simple eukaryote yeast suggests that complex signalling pathways may be circumvented through the direct interaction between individual metabolites and regulators of RNA polymerase II-mediated transcription. Biochemical and structural analyses are beginning to unravel these elegant genetic control elements.

CAD: One Step Forward, One Step Back

2010 ◽  
Vol 43 (18) ◽  
pp. 16
Author(s):  
MATTHEW R.G. TAYLOR
Keyword(s):  
One Step

One-Step Synthesis and Magnetic Phase Transformation of Ln-TM-B Alloy by Chemical Reduction

2007 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
C.W. Kim ◽  
Y.H. Kim ◽  
H.G. Cha ◽  
D.K. Lee ◽  
Y.S. Kang
Keyword(s):  
Phase Transformation ◽  
Magnetic Phase ◽  
Chemical Reduction ◽  
One Step
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