Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach

Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach

The change point identification has played a vital role in process improvement for an attribute process. This identification is able to effectively help process personnel to quickly determine the corresponding root causes and significantly improve the underlying process. Although many studies have f...

Full description

Bibliographic Details
Main Authors:	Yuehjen E. Shao, Ke-Shan Lin
Format:	Article
Language:	English
Published:	Hindawi Limited 2015-01-01
Series:	Discrete Dynamics in Nature and Society
Online Access:	http://dx.doi.org/10.1155/2015/892740

Similar Items

Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches
by: Yuehjen E. Shao
Published: (2014-01-01)

Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach
by: Yuehjen E. Shao
Published: (2013-01-01)

Hybrid Artificial Neural Networks Modeling for Faults Identification of a Stochastic Multivariate Process
by: Yuehjen E. Shao, et al.
Published: (2013-01-01)

Fault Identification in Industrial Processes Using an Integrated Approach of Neural Network and Analysis of Variance
by: Yuehjen E. Shao, et al.
Published: (2013-01-01)

Using a Time Delay Neural Network Approach to Diagnose the Out-of-Control Signals for a Multivariate Normal Process with Variance Shifts
by: Yuehjen E. Shao, et al.
Published: (2019-10-01)

A Generic Identification Strategy to Determining the Change Point of an Attribute Process
by: Lin, Keshan, et al.
Published: (2012)

An artificial neural network approach to authorship determination
by: Thirkell, Lawrence Alexander
Published: (1993)

Table and Attribute Correspondences in Multiple Databases Using Artificial Neural Networks
by: Wei-Lin Su, et al.
Published: (2002)

An Approach to Determine the Attributes of Shadow Under Artificial Lighting
by: Şensin Aydın Yağmur, et al.
Published: (2015-07-01)

A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process
by: Yuehjen E. Shao, et al.
Published: (2012-01-01)

Detecting Mean Changes in the Multivariate Normal Process Using Artificial Neural Network Approach
by: Shau-Hwa Ow, et al.

Applying Two-Stage Neural Network Based Classifiers to the Identification of Mixture Control Chart Patterns for an SPC-EPC Process
by: Yuehjen E. Shao, et al.
Published: (2017-01-01)

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches
by: Yuehjen E. Shao
Published: (2014-01-01)

Artificial Neural Networks pruning approach for geodetic velocity field determination
by: Mustafa Yilmaz

An Artificial Neural Network Approach for Monitoring High-Yield Processes
by: Wei-Jung Huang, et al.
Published: (2009)

COMPARISON OF MULTIVARIATE PROCESS MEAN SHIFT APPROACHES: MEWMA, MCUSUM, CHANGE POINT AND NEURAL NETWORK
by: Ghasemi, Mandana
Published: (2014)

Application of Artificial Neural Network to Somatotype Determination
by: Małgorzata Drywień, et al.
Published: (2021-02-01)

Artificial Neural Network for Displacement Vectors Determination
by: P. Bohmann, et al.
Published: (1997-09-01)

Flexible pavement layer moduli determination : an adaptive artificial neural network approach
by: Adeife, Michael A.
Published: (1996)

Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network
by: Xiuling Ren, et al.
Published: (2021-01-01)

Electricity Sales Forecasting Using Hybrid Autoregressive Integrated Moving Average and Soft Computing Approaches in the Absence of Explanatory Variables
by: Yuehjen E. Shao, et al.
Published: (2018-07-01)

A Novel Approach in Determining Neural Networks Architecture to Classify Data With Large Number of Attributes
by: Muhammad Ibnu Choldun Rachmatullah, et al.
Published: (2020-01-01)

Using Artificial Neural Network to Predict Physical Property of PECVD Process
by: Wen-Shan Chang, et al.
Published: (2007)

Detecting Process Variability in the Multivariate Normal Process Using Artificial Neural Network Approach
by: Tang, Wen Yen, et al.
Published: (1997)

Approximation of the process of changes in deformation of land surface using artificial neural networks
by: Mrówczyńska Maria, et al.
Published: (2018-01-01)

Approximation of the process of changes in deformation of land surface using artificial neural networks
by: Mrówczyńska Maria, et al.
Published: (2018-01-01)

Determining Purchasing Re Order Point For Inventory Problems At Commercial Environments, Using Artificial Neural Network’s (ANN)
by: Javad Amoozadeh, et al.
Published: (2011-10-01)

The Determination of the Developments of Beehives via Artificial Neural Networks
by: Raif Bayir, et al.
Published: (2018-01-01)

An Application of Artificial Neural Network for Determining Optimal Manufacturing Process Parameters and Characteristic of WEDM
by: Ferng Tian-fa, et al.
Published: (2002)

Vacuum Thermoforming Process: An Approach to Modeling and Optimization Using Artificial Neural Networks
by: Wanderson de Oliveira Leite, et al.
Published: (2018-02-01)

Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
by: Adil A. Al-Hemiri, et al.
Published: (2009-12-01)

PV Maximum Power-Point Tracking by Using Artificial Neural Network
by: Farzad Sedaghati, et al.
Published: (2012-01-01)

The Application of Artificial Neural Networks for prddicting points of Reversal in the stock market.
by: Ming-Hsuan Wu, et al.
Published: (2015)

Editorial: Artificial Neural Networks as Models of Neural Information Processing
by: Marcel van Gerven, et al.
Published: (2017-12-01)

Process identification using artificial neural network
by: Ahmad, Arshad
Published: (1995)

Welding process engineering with artificial neural networks
by: Gavrilov, Alexander I.
Published: (2005)

Process Optimization via an Artificial Neural Network
by: Horng, Yu Jing, et al.
Published: (1995)

Language processing in real and artificial neural networks.
Published: (2009)

ARTIFICIAL NEURAL NETWORK APPROACH TO TRAFFIC FLOW CONTROL
by: David E Kazaryan, et al.
Published: (2017-12-01)

Process Optimization using Simulated Annealing and Artificial Neural Network
by: Julian Jeng Lin Lin, et al.
Published: (1994)