• Journal of applied mathematics & informatics
• /
• 제42권2호
• /
• pp.257-281
• /
• 2024

In real life, a decision-maker can assign multiple values for pairwise comparison with a certain confidence level. Studies incorporating multi-choice parameters in multi-criteria decision-making methods are lacking in the literature. So, In this work, an extension of the Best-Worst Method (BWM) with multi-choice pairwise comparisons and multi-choice confidence parameters has been proposed. This work incorporates an extension to the original BWM with multi-choice uncertainty and confidence level. The BWM presumes the Decision-Maker to be fully confident about preference criteria vectors best to others & others to worst. In the proposed work, we consider uncertainty by giving decision-makers freedom to have multiple choices for preference comparison and having a corresponding confidence degree for each choice. This adds one more parameter corresponding to the degree of confidence of each choice to the already existing MCDM, i.e. multi-choice BWM and yields acceptable results similar to other studies. Also, the consistency ratio remained low within the acceptable range. Two real-life case studies are presented to validate our study on proposed models.

• 한국경영과학회지
• /
• 제20권2호
• /
• pp.61-76
• /
• 1995

The "optimal" solution for a decision making problem should be the one that best reflects the decision-maker's preference. For MADM (Multi-Attribute Decision-Making) problems, however, finding an optimal solution is difficult, especially when the number of alternatives, or that of attributes is relatively large. Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. To remedy this, some interactive methods have been proposed, but most of them require a large amount of information growing exponentially as the number of alternatives, or that of attributes increases. Therefore it is difficult for the decision-maker to maintain consistency throughout the decision making process. In this paper, an interactive method which finds optimal solutions for deterministic MADM problems with many attributes and alternatives is proposed. Instead of considering all the attributes simultaneously, this method partitions all the attributes into several mutually independent subgroups and considers one of them at each of preordered steps, where the alternatives are eliminated until the optimal one is obtained. The efficiency of the method lies in the fact that the amount of neccessary information is reduced significantly, and even further if a suboptimal solution is acceptable to the decision-maker.ion-maker.

• 대한전자공학회논문지SP
• /
• 제44권6호
• /
• pp.118-123
• /
• 2007

본 논문에서는 잡음 환경에서의 음성 향상을 위해 향상된 Global Soft Decision (GSD) 기법을 제안한다. 통계적 모델을 바탕으로 한 음성 향상과 관련한 연구에서 GSD는 음성의 꼬리 부분에서 취약하다고 알려져 있으며, 이를 개선하기 위해 Smoothed Global Likelihood Ratio (SGLR)를 바탕으로 한 새로운 음성 향상 기법을 GSD에 적용한다. 제안된 방법은 다양한 잡음 환경에서 MOS 실험을 바탕으로 기존의 연구와 비교하였으며 우수한 성능을 보여주었다.

• 한국공작기계학회논문집
• /
• 제18권1호
• /
• pp.59-67
• /
• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• 디지털산업정보학회논문지
• /
• 제19권1호
• /
• pp.109-118
• /
• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
• /
• pp.117-126
• /
• 1992

This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables. The method, called the Pairwise Comparison Stochastic Cutting Plane (PCSCP) method, combines good features from interactive multiple objective mathematical programming methods and response surface methodology. The major characteristics of the PCSCP algorithm are: (1) it interacts progressively with the decision maker (DM) to obtain his preferences, (2) it uses good experimental design to adequately explore the decision space while reducing the burden on the DM, and (3) it uses the preference information provided by the DM and the sampling error in the responses to reduce the decision space. This paper presents the basic concepts of the PCSCP method along with its performance for solving randomly selected test problems.

• 대한기계학회논문집B
• /
• 제21권11호
• /
• pp.1449-1457
• /
• 1997

Since a non-nulling method of five-hole probes is valid only when the flow angle is within the calibrated angle range, it can not be used in a complex flow field. Full angle range pressure coefficient maps show that widely used nulling methods do not guarantee correct alignment of the probe with the flow direction in the unknown complex flow field. Zone decision method and features of zone map were studied by investigating the full angle range pressure coefficient maps. A reliable and efficient new nulling algorithm using zone decision by pressure ordering is proposed and verified. Since the zone decision method by pressure ordering can decide whether the flow is within the calibration angle range or not, it is useful in wide angle nonnulling methods, too.

• 한국공간구조학회논문집
• /
• 제3권3호
• /
• pp.67-74
• /
• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• 응용통계연구
• /
• 제10권2호
• /
• pp.385-401
• /
• 1997

연속적인 생산공정에서 꾸준하면서도 작은 품질의 변화를 신속하게 탐지하는 통계적 절차로서 누적합(CUSUM) 관리도를 많이 사용하고 있다. 본 논문에서는 누적합 관리도의 평균런길이를 근사하는 방법과 누적합관리도의 통계적 설계, 즉 관리상태에서의 평균런길이가 일정한 값으로 고정되었을 경우 이를 만족하는 결정구간을 설정하는 방법을 제시한다. 또한 이 방법을 관측값이 정규분포와 지수분포를 따르는 경우에 적용시켜 그 정확성을 비교하고 있다.

• 한국멀티미디어학회논문지
• /
• 제8권6호
• /
• pp.783-789
• /
• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.