The Mahalanobis-Taguchi system - Neural network algorithm for data-mining in dynamic environments

Authors:
Ching-Lien Huang;Tsung-Shin Hsu;Chih-Ming Liu
Affiliations:
Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Kuang Fu Road, Section 2, Hsinchu, Taiwan, ROC and Department of Industrial Management, Lun ...;Department of Industrial Management, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Engineering Management, National Tsing Hua University, No. 101, Kuang Fu Road, Section 2, Hsinchu, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 9
Cited 1

Using Visualization to Support Data Mining of Large Existing Databases

Proceedings of the IEEE Visualization '93 Workshop on Database Issues for Data Visualization
Prediction of subsidence due to underground mining by artificial neural networks

Computers & Geosciences
Categorical data visualization and clustering using subjective factors

Data & Knowledge Engineering
Linear correlation discovery in databases: a data mining approach

Data & Knowledge Engineering
The basis for bibliomining: frameworks for bringing together usage-based data mining and bibliometrics through data warehousing in digital library services

Information Processing and Management: an International Journal
A framework for mining evolving trends in web data streams using dynamic learning and retrospective validation

Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics
The effect of threshold values on association rule based classification accuracy

Data & Knowledge Engineering
Genetic algorithm based framework for mining fuzzy association rules

Fuzzy Sets and Systems
Flexible online association rule mining based on multidimensional pattern relations

Information Sciences: an International Journal

Applying the Mahalanobis-Taguchi strategy for software defect diagnosis

Automated Software Engineering

Quantified Score

Hi-index	12.05

Visualization

Abstract

Data-mining analysis has two important processes: searching for patterns and model construction. From previous works finding that the Mahalanobis-Taguchi System (MTS) algorithm is successful and effective for data-mining. Conventional research in searching for patterns and modeling in data-mining is typically in a static state. Studies using a dynamic environment for data-mining are scarce. The artificial neural network (ANN) algorithm can solve dynamic condition problems. This study integrates the MTS and ANN algorithm to create the novel (MTS-ANN) algorithm that solves the pattern-recognition problems and can be applied to construct a model for manufacturing inspection in dynamic environments. From the results of the experiment, we find that the methodology of the MTS algorithm can easily solves pattern-recognition problems, and is computationally efficient as well as the ANN algorithm is a simple and efficient procedure for constructing a model of a dynamic system. The MTS-ANN algorithm is good at pattern-recognition and model construction of dynamic systems.