• Title/Summary/Keyword: Decision Function

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The Optimal Preferred Alternatives for MNDM Problems using the Taguchi's Loss function (다구찌의 손실함수를 이용한 다망목특성을 가지는 의사결정문제의 최적 선호대안 결정)

  • Lee, Kang-In
    • Journal of Korean Institute of Industrial Engineers
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    • v.24 no.4
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    • pp.493-502
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    • 1998
  • The purpose of this paper is to propose an interactive method, which is designed to select the optimal preferred alternatives for the MNDM(Multi-N type Decision- Making) problems with the-Nominal-the-best characteristics. The basic idea of the paper is essentially to eliminate inefficient alternatives based on the concept of the lass function and the cutting range instead of using the utility/value function on the group of attributes that can be considered as important by the decision-maker. As a result, the method proposed in the paper for MNDM problems can be significant in that the change of characteristics is transformed into the size of loss, which can be relatively easy to understand by decision-makers.

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APPLICATIONS OF SIMILARITY MEASURES FOR PYTHAGOREAN FUZZY SETS BASED ON SINE FUNCTION IN DECISION-MAKING PROBLEMS

  • ARORA, H.D.;NAITHANI, ANJALI
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.897-914
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    • 2022
  • Pythagorean fuzzy sets (PFSs) are capable of modelling information with more uncertainties in decision-making problems. The essential feature of PFSs is that they are described by three parameters: membership function, non-membership function and hesitant margin, with the total of the squares of each parameter equal to one. The purpose of this article is to suggest some new similarity measures and weighted similarity measures for PFSs. Numerical computations have been carried out to validate our proposed measures. Applications of these measures have been applied to some real-life decision-making problems of pattern detection and medicinal investigations. Moreover, a descriptive illustration is employed to compare the results of the proposed measures with the existing analogous similarity measures to show their effectiveness.

Fuzzy Decision Making System

  • Karpovsky, Ephim Ja
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.806-809
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    • 1993
  • This paper focuses on the usage of the fuzzy set theory in decision making systems. The approach to calculation of generalized membership function, based on application of method of principal components is proposed. For solving of the problem of fuzzy forecasting the development of Bayes procedure is used. The structure of decision making system, in which following procedures are fulfilled, is discussed.

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The Effects of Decision Style(Feeling vs. Thinking) on the Use of GDSS (의사결정스타일이 GDSS활용에 미치는 영향)

  • Choi, Moo-Jin
    • Asia pacific journal of information systems
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    • v.10 no.1
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    • pp.1-18
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    • 2000
  • One stream of the GDSS(Group Decision Support System) research is to investigate how GDSS affects decision performances of small groups according to task types, support features, meeting facilitation modes and meeting environments. But little study has investigated the effects of group member characteristics on group decision processes and outcomes depending upon whether GDSS is provided or not. To date, most GDSS studies have not controlled group member characteristics(e,g. personality, sex, decision style) in laboratory experiments. However, this study included the decision styles of group members as an independent variable. Therefore, this study investigated how differently members of two different decision styles perceive the use of GDSS in small group meetings through lab experiments. The two decision styles are feeling(F) style and thinking(T) style. We found that the effect of GDSS is a function of individual's decision style only in the communication thoroughness variable. The decision style is a statistically significant factor that can mediate the effects of the group support technology on the perceived communication thoroughness. Specifically, the GDSS is positively related to participants' perception about satisfaction on decision process, goal achievement, communication thoroughness, degree of influence-outward and effort for achieving meeting goals.

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Conceptual Design of the Artificial Intelligence based Tactical Command Decision Support System using the Functional Analysis Method (기능분석법을 이용한 인공지능 기반 전술제대 지휘결심지원체계의 개념설계)

  • Choi, Keun Ha
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.6
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    • pp.650-658
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    • 2020
  • The research of the AI-based command decision support system was insufficient both quantitatively and qualitatively. In particular, in Korea, there was no research on concrete concept design at the current concept research level. This paper proposed the conceptual design of a tactical echelon command decision support system based on artificial intelligence(AI) according to the current army's doctrine of the operation process. The suggested conceptual design clarified the problem and proposed an appropriate process for design, and applied the function analysis method among rational techniques that enable conceptual design systematically.

The Preferred Alternative for MLDM Problems using the Signal-to-Noise Ratios (신호대 잡음비를 이용한 MLDM 문제의 선호대안 선정)

  • 이강인
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.26 no.4
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    • pp.72-81
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    • 2003
  • The purpose of this paper is to propose an interactive method, which is designed to select the optimal preferred alter-native for the MLDM(Multiple-the Larger-the better type Decision-Making) problems with the-larger-the-better quality characteristics. The basic idea of the paper is essentially to eliminate inefficient alternative based on the concept of Taguchi Signal-to-Noise ratios and the cutting range instead of using UVF(Utility/value Function) on the group of attributes that can be considered importantly by the decision makers. As a result, the method proposed in the paper for MLDM problems can be significant in that the change of characteristics is transformed into the size of Signal-to-Noise ratio, which can be relatively easy to understand by decision makers.

REDISCOVERING THE LEXICOGRAPHIC LINEAR GOAL PROGRAMMING MULTIPLEX MODEL

  • Park, Byung-Kwon;Lee, Jae-Jung
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.2
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    • pp.63-73
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    • 2001
  • An alternative approach to formulating a special class of linear goal programming (LGP) models is presented. We propose a formulation of the LGP model that can include the decision variables in the objective function. We specifically propose that the position of the decision variables in the objective function be used to eliminate goal constraints whose sole purpose is to indirectly optimize decision variables. For the select group of LGP problems wherever indirect optimization of decision variables are sought, the alternative LGP model formulation is able to reduce the size of these LGP models and in turn the computational effort required for their solution.

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Microprocessor Control of a Prosthetic Arm by EMG Pattern Recognition (EMG 패턴인식을 이용한 인공팔의 마이크로프로세서 제어)

  • Hong, Suk-Kyo
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.33 no.10
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    • pp.381-386
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    • 1984
  • This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

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Seamless Mobility of Heterogeneous Networks Based on Markov Decision Process

  • Preethi, G.A.;Chandrasekar, C.
    • Journal of Information Processing Systems
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    • v.11 no.4
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    • pp.616-629
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    • 2015
  • A mobile terminal will expect a number of handoffs within its call duration. In the event of a mobile call, when a mobile node moves from one cell to another, it should connect to another access point within its range. In case there is a lack of support of its own network, it must changeover to another base station. In the event of moving on to another network, quality of service parameters need to be considered. In our study we have used the Markov decision process approach for a seamless handoff as it gives the optimum results for selecting a network when compared to other multiple attribute decision making processes. We have used the network cost function for selecting the network for handoff and the connection reward function, which is based on the values of the quality of service parameters. We have also examined the constant bit rate and transmission control protocol packet delivery ratio. We used the policy iteration algorithm for determining the optimal policy. Our enhanced handoff algorithm outperforms other previous multiple attribute decision making methods.

Performance Enhancement of Decision Directed SNR Estimation by Correction Scheme of SNR Estimation Error (결정지향 SNR 추정방식에서의 추정오차 보정기법을 통한 SNR 추정성능개선)

  • Kwak, Jae-Min
    • Journal of Advanced Navigation Technology
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    • v.16 no.6
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    • pp.982-987
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    • 2012
  • In this paper, the SNR estimation error of Decision Directed SNR estimation method in AWGN is investigated, which uses samples received in reference decision region. In communication system receiver, when SNR estimation scheme using error vectors between ideal sample points and received sample points of reference region is adopted, the samples contain incorrectly received samples due to AWGN. Consequently, the mean of estimated reference constellation point is shifted and Decision Directed SNR estimation is inaccurately performed. These effects are explained by modified probability density function and difference between actual SNR and estimated SNR is theoretically derived and quantatively analyzed. It is proved that SNR estimation error obtained through computer simulation is matched up with derived one, and SNR estimation performance is enhanced significantly by adopting suggested correction scheme.