• 제목/요약/키워드: decision problem

검색결과 2,269건 처리시간 0.036초

Hierarchical Resource Management Framework and Multi-hop Task Scheduling Decision for Resource-Constrained VEC Networks

  • Hu, Xi;Zhao, Yicheng;Huang, Yang;Zhu, Chen;Yao, Jun;Fang, Nana
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3638-3657
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    • 2022
  • In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.

Xgboosting 기법을 이용한 실내 위치 측위 기법 (Indoor positioning system using Xgboosting)

  • 황치곤;윤창표;김대진
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.492-494
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    • 2021
  • 기계학습에서 분류를 위한 기법으로 의사결정트리 기법을 이용한다. 그러나 의사결정트리는 과적합의 문제로 성능이 저하되는 문제가 있다. 이러한 문제를 해결하기 위해 여러 개의 부트스트랩을 생성하여 각 자료를 모델링하여 학습하는 Bagging기법, 샘플링한 데이터를 모델링하여 가중치를 조정하여 과적합을 감소시키는 Boosting과 같은 기법으로 이를 해결할 수 있다. 또한, 최근에 Xgboost 기법이 등장하였다. 이에 본 논문에서는 실내 측위를 위한 wifi 신호 데이터를 수집하여 기존 방식과 Xgboost에 적용하고, 이를 통한 성능평가를 수행한다.

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시스템 다이나믹스를 이용한 지식 기반 의사결정 (Knowledge-based Decision Making using System Dynamics)

  • 김희웅;곽상만
    • 산업공학
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    • 제13권1호
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    • pp.17-28
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    • 2000
  • As knowledge has been recognized as a new resource in gaining organizational competitiveness, Knowledge Management (KM) is suggested as a method to manage and apply knowledge for business management. KM research, however, has focused on identifying, storing, and distributing the transaction-related knowledge in an organization. There has been little research on applying the knowledge to decision-making or strategy development that is the main task of business management. The application of knowledge to decision making has higher impact on organizational performance rather than just the knowledge management for process transaction. In this research, we suggest System Dynamics (SD) for the knowledge-based decision-making. Based on the modeling method of SD, we can translate partial and implicit knowledge resident in individual's mental model into organized explicit knowledge. The simulation test of the organized knowledge model enables decision-makers to understand the structure of the target problem and its behavior mechanism, which facilitates effective decision-making. We will compare the proposed method and other KM methods and discuss this research based on the application case to a real telecommunication company.

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레저산업의 고객관계관리 문제에서 기상예보의 정보가치를 최대화시키는 의사결정전략 분석 (A Decision-making Strategy to Maximize the Information Value of Weather Forecasts in a Customer Relationship Management (CRM) Problem of the Leisure Industry)

  • 이중우;이기광
    • 경영과학
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    • 제27권1호
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    • pp.33-43
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    • 2010
  • This paper presents a method for the estimation and analysis of the economic value of weather forecasts for CRM decision-making problems in the leisure industry. Value is calculated in terms of the customer's satisfaction returned from the user's decision under the specific payoff structure, which is itself represented by a customer's satisfaction ratio model. The decision is assessed by a modified cost-loss model to consider the customer's satisfaction instead of the loss or cost. Site-specific probability and deterministic forecasts, each of which is provided in Korea and China, are applied to generate and analyze the optimal decisions. The application results demonstrate that probability forecasts have greater value than deterministic forecasts, provided that the users can locate the optimal decision threshold. This paper also presents the optimal decision strategy for specific customers with a variety of satisfaction patterns.

전략적 과제에 대한 지식기반의 의사결정 (Knowledge-based Decision Making on Strategic Problems)

  • 임남홍
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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    • pp.595-598
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    • 2004
  • In recognizing knowledge as a new resource in gaining organizational competitiveness, knowledge management suggests a method in managing and applying knowledge for improving organizational performance. Much knowledge management research has focused on identifying, storing, and disseminating process related knowledge in an organized manner. Applying knowledge to decision making has a significant impact on organizational performance than solely processing transactions for knowledge management. In this research, we suggest a method of knowledge-based decision-making using system dynamics, with an emphasis to strategic problems. The proposed method transforms individual mental models into explicit knowledge by translating partial and implicit knowledge into an integrated knowledge model. The scenario-based test of the organized knowledge model enables decision-makers to understand the structure of the target problem and identify its basic cause, which facilitates effective decision-making. This method facilitates the linkage between knowledge management initiatives and achieving strategic goals and objectives of an organization.

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유아 의사결정력과 자기주도 학습능력 간의 관계 연구 (A Study of the Relationship between Decision Making Abilities in Young Children and Self-directed Learning Abilities)

  • 박지영
    • 아동학회지
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    • 제33권6호
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    • pp.71-84
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    • 2012
  • The purpose of this study is to analyze the relationship between decision making abilities young children and their self-directed learning abilities. A survey was carried out using 160 young children in the J region. The collected data were analyzed by Pearson correlation and multiple regression techniques using the SPSS statistics program. The conclusions are as follows : First, decision making abilities in young children exhibited a positive correlation with their self-directed learning abilities. Second, decision making abilities in young children were an influential variable in terms of their self-directed learning abilities. As a result, decision making abilities in young children were an important variable in predicting their self-directed learning abilities.

Lindley Type Estimation with Constrains on the Norm

  • Baek, Hoh-Yoo;Han, Kyou-Hwan
    • 호남수학학술지
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    • 제25권1호
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    • pp.95-115
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    • 2003
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p{\geq}4)$ under the quadratic loss, based on a sample $X_1,\;{\cdots}X_n$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $||{\theta}-{\bar{\theta}}1||$ is known, where ${\bar{\theta}}=(1/p)\sum_{i=1}^p{\theta}_i$ and 1 is the column vector of ones. When the norm is restricted to a known interval, typically no optimal Lindley type rule exists but we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

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탈중앙화된 자율 조직 의사결정을 위한 도구 (A Decision Making Tool for Decentralized Autonomous Organization)

  • 이요셉;박용범
    • 반도체디스플레이기술학회지
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    • 제19권2호
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    • pp.1-10
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    • 2020
  • Blockchain enabled Decentralized Autonomous Organization (DAO), a new form of organization with conveying its core value - trust. Token holders who are participating DAO's governance share their thoughts, information, and ideas in online forum. But it is problem that chronological form of DAO's online forum makes token holders hard to find crucial information, meaning that many of them might not understand what is happening discussion. In this paper, we studied not only a decision making process which feature is iteration, visualization, and applicable to DAO with 6 steps in total but also a decision making tool which is based on the process of this paper. The tool has features to help participants such as voting model, visualization features which gives guidance to them for their decision during the process. Our experiment showed that the process and tool is somewhat reasonable, and the information during the process is effective for participants. This work is expected to be applied to current DAOs to make a decision among the token holders.

AHP 기법에의한 고속선의 최적 기관 시스템 결정법 (Decision Method of Optimal Engine System for High-Speed Ship by Analytical Hierarchy Process)

  • H.B. Ro
    • Journal of Advanced Marine Engineering and Technology
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    • 제22권3호
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    • pp.381-395
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    • 1998
  • The purpose of this study is to determine the optimal gas turbine system for special purpose ships. First we generate critical evaluation criteria an construct their hierarchical structure. The criteria consist of qualitative ones as well as the economic factor. Then AHP is applied to solve the decision making problem AHP gibes good results different from those only by the economic evaluation methods. And during the analysis, the procedure produces many useful informations to the decision making. The results shows that AHP is an appropriate method for these kinds of problems such as the system selection.

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MULTICRITERIA MODELS FOR GROUP DECISION MAKING : COMPROMISE PROGRAMMING VS. THE ANALYTIC HIERACHY PROCESS

  • Kwak, N.K.;McCarthy, Kevin J.
    • 한국경영과학회지
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    • 제16권1호
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    • pp.97-112
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    • 1991
  • This paper describes two contrasting approaches to group decision making involving multiple criteria. A compromise programming method and the analytic hierarchy process are analyzed and compared by using an illustrative example of a computer model selection problem to demonstrate their usefulness as a viable tool for group decision making. This paper further considers some extensions and modifications of there two methods for future study.

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