• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.55-61
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• 2003

The purpose of this paper is to propose a method for selecting the preferred alternatives of Multiple- Attribute Decision-Making(MADM) problem using the Entropy measure. A decision-maker who wants to estimate exactly the weight to be applied to her/his MADM problem is usually confronted with the embarrassing situation where, although there exist a variety of weighting methods, it is hard to find a right procedure to choose a pertinent value To remedy this uncomfortable situation, the Entropy measure commonly used in information theory, Is proposed as a tool that can be used by decision-makers to more efficiently select the preferred alternatives. As a result, the method proposed in the paper can be significant in that relatively easy to understand by decision-makers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.11-23
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• 1998

This paper presents a more efficient evaluation of alternatives by use of multi-criteria decision making methodlogy under fuzzy intersectional dependence relations. The performance evaluation of most systems such as weapons, enterprise systems etc. are multiple criteria decision making problems. The descriptions and judgements on these systems are usually linguistic and fuzzy. The traditional methods of Analytic Hierarchy Process(AHP) are mainly used in crisp(non-fuzzy) decision applications with a very unbalanced scale of judgements and rank reversal. To overcome these problems, we will propose a new, general decision making method for evaluation models using fuzzy AHP(FAHP) under fuzzy intersectional dependence relations. The T.M.S alternatives A, B and C will be evaluted by the Fuzzy Analytic Hierachy Process (FAHP) based on entropy weight in this study. We will use symmetric triangular fuzzy numbers to indicate the relative strength of the elements in the hierachy and degree of intersection between criteria. These problems are evaluated by five criteria : tactical criteria, technology criteria, maintenance criteria, economy criteria, advacement criteria.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.855-861
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• 2005

Every public agency governing infrastructure has to plan effectively for rehabilitation of existing facilities within the constraints of the capital program. Numerous technical, social, political, financial, and management constraints govern the decision to rehabilitate a facility. However, without a systematic procedure for selecting facilities for rehabilitation, within the prevailing constraints, it is possible that the funds available for rehabilitation might be suboptimized. Therefore, a decision support system that assists the user in selecting facilities for rehabilitation while considering the technical, social, financial, and political and management constraints will be useful in the decision-making process. This paper compares the Analytical Hierarchy Process (AHP) with the Swing Weight method used to prioritize functional criteria for suburban station rehabilitation. This paper also contains a brief discussion about the relevance of the Multi Attribute utility theory in developing a decision model for the problem at hand. The results of this paper provides the user with a decision support system that would prioritize the stations in order of their weights obtained by a systematic evaluation of various criteria and sub-criteria involved in the decision making process

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.605-613
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• 2010

In this study, Impact factors are represented and barrier height of compact car road of safety barrier is suggested through the investigation of applying problems of existed standard of general car road. For this, traffic accidents analysis is performed and based on the analysis, impact vehicle weight, impact Angle, crash velocity, and barrier height are investigated. For the decision of impact angle, analysis is carried out by comparison of RISER and 2-lines expressway accidents data. Through this, higher-impact angle is suggested. Vehicle weight data of sub-compact car, small vehicle, medium and large vehicle, SUV, small truck is surveyed and analyzed. Based on the accident accumulation rate, regression analysis of vehicle weight impact and impact velocity is performed. Also, based on the cumulative rate of vehicle weight on expressways near Seoul, barrier height of compact car road is calculated. It is noted that the results of this study will be contributed to the decision of barrier type.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.79-88
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• 2015

This study focused on the idea that consumers who are dissatisfied with their body form tend to be more interested in weight control behavior. This research connects this relationship with consumers' risk perception on the internet and consequent decision hesitation behavior. Empirical results extracted three factors of weight control behavior: diet, physical treatment, and medication and exercise. Weight control behavior was different by gender but not by age. Consumers who were dissatisfied with their body form were likely to do exercise, but other types of dissatisfaction (weight dissatisfaction and height dissatisfaction) were not significantly related to weight control behavior. Weight dissatisfaction influenced perceived size risk significantly when shopping online. Diet, physical treatment, and medication had significant influence on perceived size risk when shopping online. Perceived size risk had significant influence on decision delay and offline switch behavior. This study took a convergence approach, which connects consumer characteristics with online shopping behavior.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7971-7977
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• 2015

This paper attempts to select the attributes of job creation and to rank them for evaluation of companies' job creation. And the results of this paper are expected to provide the information for the polices of job creation. In doing so, this paper applies fuzzy decision making analysis that reflects ambiguity and uncertainty in decision-making process. According to the results, the weight of quality of employment is similar with that of quantity of employment. In addition, annual employment growth rate, annual net employment are ranked as first and the percentage of irregular employment, the average length of employment of all workers, average monthly wages of all workers, and employment growth over sales growth rate are next ranked.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1283-1293
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• 2014

In ubiquitous environment, data are changing rapidly and new data is coming as times passes. And sometimes all of the past data will be lost if there is not sufficient space in memory. Therefore, there is a need to make rules and combine it with new data not to lose all the past data or to deal with large amounts of data. In making decision trees and extracting rules, the weight of each of rules is generally determined by the total number of the class at leaf. The computational problem of finding a minimum finite state acceptor compatible with given data is NP-hard. We assume that rules extracted are not correct and may have the loss of some information. Because of this precondition. this paper presents a new approach for refining rules. It controls their weight of rules of previous knowledge or data. In solving rule refinement, this paper tries to make a variety of rules with pruning method with majority and minority properties, control weight of each of rules and observe the change of performances. In this paper, the decision tree classifier with extended data expression having static weight is used for this proposed study. Experiments show that performances conducted with a new policy of refining rules may get better.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.1
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• pp.25-33
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• 2020

Multipath routing protocols with unmanned aerial vehicles have been proposed to improve reliability in tactical ad hoc networks. Most of existing studies tend to establish the paths with multiple metrics. However, these approaches suffer from link loss and congestion problems according to the network condition because they apply same metric for both ground and air path or employ the simple weight value to combine multiple metrics. To overcome this limitation, in this study, we propose new routing metrics for path over unmanned aerial vehicles and use the multi-criteria decision making (MCDM) method to determine the weight factors between multiple metrics. For the case studies, we extend the ad-hoc on-demand distance vector protocol and propose a strategy for modifying the route discovery and route recovery procedure. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in tactical ad hoc networks.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.1-8
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• 2001

In the DS/CDMA mobile communication systems, the parallel interference canceller is used in order to reduce the multiple access interference and the multipath fading. It is needed the accurate interference estimate in the multistage parallel cancellation. In this paper, the adaptive cancellation method and the new tentative decision device arc proposed and the performance is analyzed. The adaptive cancellation method uses the normalized least mean square(NLMS) algorithm to calculate the weight adaptively, and new tentative decision device uses the hyperbolic tangent decision with null zone. Computer simulation shows that the proposed scheme has the improved performance and the number of user is increased 48% compared with the conventional receiver.

• ETRI Journal
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• v.39 no.5
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• pp.621-631
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• 2017

Abnormal samples are usually difficult to obtain in production systems, resulting in imbalanced training sample sets. Namely, the number of positive samples is far less than the number of negative samples. Traditional Support Vector Machine (SVM)-based anomaly detection algorithms perform poorly for highly imbalanced datasets: the learned classification hyperplane skews toward the positive samples, resulting in a high false-negative rate. This article proposes a new imbalanced SVM (termed ImSVM)-based anomaly detection algorithm, which assigns a different weight for each positive support vector in the decision function. ImSVM adjusts the learned classification hyperplane to make the decision function achieve a maximum GMean measure value on the dataset. The above problem is converted into an unconstrained optimization problem to search the optimal weight vector. Experiments are carried out on both Cloud datasets and Knowledge Discovery and Data Mining datasets to evaluate ImSVM. Highly imbalanced training sample sets are constructed. The experimental results show that ImSVM outperforms over-sampling techniques and several existing imbalanced SVM-based techniques.