• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.311-317
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• 2007

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are so depended on jury test very much that they result in many difficulties. So, to reduce jury test weight, we suggested a new method using Mahalanobis distance for SQ evaluation. And, optimal characteristic values influenced on the result of the SQ evaluation were derived by signal to noise ratio(SN ratio) of the Taguchi method. Finally, the new method to evaluate SQ is constructed using Mahalanobis-Taguchi system(MTS). Furthermore, the MTS method for SQ evaluation was compared by the result of SQ grade table at the previous study and their virtues and faults introduced.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.318-321
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• 2007

Since human listening is very sensitive to sound, a subjective index of a sound quality is required. Therefore, in the analysis for each situation, the sound evaluation is composed with sound quality factor. Many researchers spends their effort to make a more reliable and more accurate of sound in term of sound quality index for various system noise. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are so depended on jury test very much that they result in many difficulties. So, to reduce jury test weight, we suggested a new method using Mahalanobis distance for SQ evaluation. Threrefore, in this study Mahalanobis distance for the vehicle interior noise was derived using the objective SQ except jury test. Finnaly, the results of the SQ evaluation was analyzed discrimination between reference and abnormal group.

• 응용통계연구
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• 제26권2호
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• pp.223-236
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• 2013

미국 프로야구(Major League Baseball) 명예의 전당의 입성과 탈락을 예측할 수 있는 여러 가지 통계적인 분류분석법을 실시하고 그 결과의 정확성을 비교하였다. 이를 위해 명예의 전당 가입 조건을 만족하는 타자들 중 1980년 이후 기록된 데이터의 17개의 독립변수를 사용하여 분류분석에서 널리 사용되는 기준으로 판별분석, 로지스틱 회귀분석과 상대적으로 최근에 제안된 Mahalanobis-Taguchi System(MTS)을 실시하여 비교하였다. 이 세 가지 방법 중 MTS가 상대적으로 더 나은 효율을 보였으며 이는 다변량 관측 값이 방향성이 없어 속성에 따른 도형적 그룹을 형성하지 못하는 경우에 효율적인 MTS의 특성에 의한 것으로 판단된다.

• International Journal of Quality Innovation
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• 제3권2호
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• pp.113-131
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• 2002

The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

• 한국소음진동공학회논문집
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• 제18권1호
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• pp.57-60
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• 2008

Since human listening is very sensitive to sound, for evaluating of a sound quality is required. Therefore, in the analysis for each situation, the sound evaluation is composed with sound quality factor. My researchers spends their effort to make a more reliable and more accurate of sound in term of sound quality index for various system noise. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are highly dependent on jury test and have many difficulties due to various environmental factors. So, to reduce jury test weight. we suggested a new method using Mahalanobis distance for SQ evaluation. Threrefore, in this study Mahalanobis distance for the vehicle interior noise was derived using the objective SQ except jury test. Finnaly, the results of the SQ evaluation was analyzed discrimination between reference and abnormal group.

• 제어로봇시스템학회논문지
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• 제5권7호
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• pp.814-820
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• 1999

We propose a target identification algorithm for visual tracking. Target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrical relationship between model segments and extracted line segments.

• 한국자동차공학회논문집
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• 제17권2호
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• pp.165-170
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• 2009

Pressure ripple, vibration and noise level are measured in each parts of the power steering system. MD(Mahalanobis Distance) is calculated by using MTS(Mahalanobis Taguchi System) with measured data, and noise sensitive components are selected. The components applied detail design parameters are made and data is measured. After that MD is calculated also. Mean value and SN ratio can be obtained from the MD. Effective noise reduction technique and dominant design parameters in hydraulic power steering system are introduced.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 추계학술대회
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• pp.233-243
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• 2010

Mahalanobis Taguchi System (MTS) is a pattern information technology, which has been used in different diagnostic applications to make quantitative decisions by constructing a multivariative measurement scale using data analytic methods. In MTS approach, Mahalanobis distance (MD) is used to measure the degree of abnormality of patterns and principles of Taguchi methods are used to evaluate accuracy of predictions based on the scale constructed. The advantage of MD is that it takes into consideration the correlations between the variables and this consideration is very important in pattern analysis. The purpose of this study is constructing admission diagnosis system and define the effect of admission requirements for student's academic accomplishment.

• 대한기계학회논문집A
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• 제32권7호
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• pp.556-560
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• 2008

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, we present a study on the application of vibration signals to diagnose faults for a Rotating Machinery using the Mahalanobis Distance-Taguchi System. RMS, Crest Factor and Kurtosis that is known as the Statistical Methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 춘계종합학술대회
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• pp.305-308
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• 2003

본 논문에서는 Fuzzy-ART (Fuzzy-Adaptive Resonance Theory) 신경회로망의 패턴인식 성능을 개선하기 위해 Mahalanobis 거리를 이용한 타원형 fuzzy-ART 신경회로망을 제안한다. 제안한 방식은 벡터공간상에서 패턴의 영역을 규정하기 위해 Mahalanobois 거리 개념을 이용한다. 제안한 방식의 유용성을 확인하기 위해 얼굴인식에 적용하였으며, 기존의 방식과 비교 검토한 결과 유용성을 확인하였다.