Journal ArticleDOI
Binary ant colony optimization applied to variable screening in the Mahalanobis-Taguchi System
TLDR
The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm and a comparison with respect to binary particle swarm optimization algorithm is presented.Abstract:
This work presents the application of the Mahalanobis-Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.read more
Citations
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Journal ArticleDOI
Mahalanobis Taguchi system: a review
TL;DR: A review on the concepts and operations of the Mahalanobis-Taguchi system (MTS) was provided as a new method in the field of pattern recognition, multivariable diagnosis, and forecasting as mentioned in this paper.
Journal ArticleDOI
Mahalanobis-Taguchi system applied to variable selection in automotive pedals components using Gompertz binary particle swarm optimization
TL;DR: This work presents the application of the Mahalanobis-Taguchi system (MTS) to variable detection in the manufacturing process of automotive pedals components and a numerical comparison with respect to other common version of binary particle swarm and binary ant colony optimization algorithms is presented.
Journal ArticleDOI
Enhancement of Mahalanobis-Taguchi System via Rough Sets based Feature Selection
TL;DR: The current research presents a methodology for classification based on Mahalanobis Distance and Association Mining using Rough Sets Theory and two new variants of MTS classifier are developed and their performance in terms of accuracy of classification is evaluated on test datasets from five case studies.
Journal ArticleDOI
Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades
TL;DR: A two-stage MCS classification approach, coupled with Binary Particle Swarm Optimization, is proposed to optimize the process of selecting the most significant features and to search for the optimal decision boundary to discriminate healthy and unhealthy components.
Journal ArticleDOI
A Theoretical Survey on Mahalanobis-Taguchi System
TL;DR: This paper reviews the literature related to developing and improving MTS theory, and presents and analyzes the research results in terms of MD, SNR, Mahalanobis Space (MS), feature selection, threshold, multi-class MTS, and comparison with other methods.
References
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Book ChapterDOI
Ant Colony Optimization: Overview and Recent Advances
Marco Dorigo,Thomas Stützle +1 more
TL;DR: This chapter reviews developments in ACO and gives an overview of recent research trends, including the development of high-performing algorithmic variants and theoretical understanding of properties of ACO algorithms.
Proceedings ArticleDOI
A novel binary particle swarm optimization
TL;DR: This algorithm is shown to be a better interpretation of continuous PSO into discrete PSO than the older versions and a number of benchmark optimization problems are solved using this concept and quite satisfactory results are obtained.
Book
The Mahalanobis-Taguchi Strategy: A Pattern technology System
Genichi Taguchi,Rajesh Jugulum +1 more
TL;DR: In this article, the authors present an overview of the state of the art in multidimensional systems and their application in the medical domain, including the use of MTS and MTGS.
Journal ArticleDOI
Development of a hybrid methodology for dimensionality reduction in Mahalanobis-Taguchi system using Mahalanobis distance and binary particle swarm optimization
Avishek Pal,Jhareswar Maiti +1 more
TL;DR: This research study proposes a dimensionality reduction method by addressing the problem as feature selection exercise of MTS using data from an Indian foundry shop to test the mathematical model and the swarm heuristic.
Journal Article
An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition
Elizabeth A. Cudney,Jungeui Hong,Rajesh Jugulum,Kioumars Paryani,Kenneth M. Ragsdell,Genichi Taguchi +5 more
TL;DR: In this paper, the authors compare the ability of the Mahalanobis-Taguchi System and a neural-network to discriminate using small data sets, and examine the discriminant ability as a function of data set size.
Related Papers (5)
Development of a hybrid methodology for dimensionality reduction in Mahalanobis-Taguchi system using Mahalanobis distance and binary particle swarm optimization
Avishek Pal,Jhareswar Maiti +1 more