• Title/Summary/Keyword: 파레토 효율성

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Generating of Pareto frontiers using machine learning (기계학습을 이용한 파레토 프런티어의 생성)

  • Yun, Yeboon;Jung, Nayoung;Yoon, Min
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.3
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    • pp.495-504
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    • 2013
  • Evolutionary algorithms have been applied to multi-objective optimization problems by approximation methods using computational intelligence. Those methods have been improved gradually in order to generate more exactly many approximate Pareto optimal solutions. The paper introduces a new method using support vector machine to find an approximate Pareto frontier in multi-objective optimization problems. Moreover, this paper applies an evolutionary algorithm to the proposed method in order to generate more exactly approximate Pareto frontiers. Then a decision making with two or three objective functions can be easily performed on the basis of visualized Pareto frontiers by the proposed method. Finally, a few examples will be demonstrated for the effectiveness of the proposed method.

Game Theory Application in Wetland Conservation Across Various Hypothetical City Sizes (다양한 이론적 도시규모에서의 습지 보전을 위한 게임 이론 적용)

  • Ran-Young Im;Ji Yoon Kim;Yuno Do
    • Journal of Wetlands Research
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    • v.26 no.1
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    • pp.10-20
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    • 2024
  • The conservation and restoration of wetlands are essential tasks for the sustainable development of human society and the environment, providing vital benefits such as biodiversity maintenance, natural disaster mitigation, and climate change alleviation. This study aims to analyze the strategic interactions and interests among various stakeholders using game theory and to provide significant grounds for policy decisions related to wetland restoration and development. In this study, hypothetical scenarios were set up for three types of cities: large, medium, and small. Stakeholders such as governments, development companies, environmental groups, and local residents were identified. Strategic options for each stakeholder were developed, and a payoff matrix was established through discussions among wetland ecology experts. Subsequently, non-cooperative game theory was applied to analyze Nash equilibria and Pareto efficiency. In large cities, strategies of 'Wetland Conservation' and 'Eco-Friendly Development' were found beneficial for all stakeholders. In medium cities, various strategies were identified, while in small cities, 'Eco-Friendly Development' emerged as the optimal solution for all parties involved. The Pareto efficiency analysis revealed how the optimal solutions for wetland management could vary across different city types. The study highlighted the importance of wetland conservation, eco-friendly development, and wetland restoration projects for each city type. Accordingly, policymakers should establish regulations and incentives that harmonize environmental protection and urban development and consider programs that promote community participation. Understanding the roles and strategies of stakeholders and the advantages and disadvantages of each strategy is crucial for making more effective policy decisions.

Evaluation on the Reliability Attributes of Finite Failure NHPP Software Reliability Model Based on Pareto and Erlang Lifetime Distribution (파레토 및 어랑 수명분포에 근거한 유한고장 NHPP 소프트웨어 신뢰성모형의 신뢰도 속성에 관한 평가)

  • Min, Kyung-il
    • Journal of Industrial Convergence
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    • v.18 no.3
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    • pp.19-25
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    • 2020
  • In the software development process, software reliability evaluation is a very important issue. In particular, finding the optimal development model that satisfies high reliability is the more important task for software developers. For this, in this study, Pareto and Erlang life distributions were applied to the finite failure NHPP model to evaluate the reliability attributes. For this purpose, parametric estimation is applied to the maximum likelihood estimation method, and nonlinear equations are calculated using the bisection method. As a result, the Erlang model showed better performance than the Pareto model in the evaluation of the strength function and the mean value function. Also, as a result of inputting future mission time and evaluating reliability, the Erlang model showed an effectively high trend together with the Pareto model, while the Goel-Okumoto basic model showed a decreasing trend. In conclusion, the Erlang model is the best model among the proposed models. Through this study, it is expected that software developers will be able to use it as a basic guideline for exploring and evaluating the optimal software reliability model.

The Comparative Study for NHPP of Truncated Pareto Software Reliability Growth Model (절단고정시간에 근거한 파레토 NHPP 소프트웨어 신뢰성장모형에 관한 비교 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.12 no.1
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    • pp.9-16
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    • 2012
  • Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

Multi-Objective Micro-Genetic Algorithm for Multicast Routing (멀티캐스트 라우팅을 위한 다목적 마이크로-유전자 알고리즘)

  • Jun, Sung-Hwa;Han, Chi-Geun
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07a
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    • pp.916-918
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    • 2005
  • 다목적 최적화 문제의 목표는 다양한 파레토 최적해(Pareto Optimal Solution)을 찾는데 있으며, 마이크로-유전자 알고리즘(Micro-Genetic Algorithm)은 단순 유전자 알고리즘(Simple Genetic Algorithm)에 비해 소수의 유전자들만을 선별하여 진화시키는 방식으로 효율성을 극대화시킨다. 본 논문에서는 다양한 목적을 동시에 최적화하는 다목적 멀티캐스트 라우팅 문제를 해결하기 위해서 다목적 유전자 알고리즘과 마이크로-유전자 알고리즘을 결합한 다목적 마이크로-유전자 알고리즘을 적용하였다.

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Efficient Bayesian Inference on Asymmetric Jump-Diffusion Models (비대칭적 점프확산 모형의 효율적인 베이지안 추론)

  • Park, Taeyoung;Lee, Youngeun
    • The Korean Journal of Applied Statistics
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    • v.27 no.6
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    • pp.959-973
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    • 2014
  • Asset pricing models that account for asymmetric volatility in asset prices have been recently proposed. This article presents an efficient Bayesian method to analyze asset-pricing models. The method is developed by devising a partially collapsed Gibbs sampler that capitalizes on the functional incompatibility of conditional distributions without complicating the updates of model components. The proposed method is illustrated using simulated data and applied to daily S&P 500 data observed from September 1980 to August 2014.

Pareto Ratio and Inequality Level of Knowledge Sharing in Virtual Knowledge Collaboration: Analysis of Behaviors on Wikipedia (지식 공유의 파레토 비율 및 불평등 정도와 가상 지식 협업: 위키피디아 행위 데이터 분석)

  • Park, Hyun-Jung;Shin, Kyung-Shik
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.19-43
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    • 2014
  • The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

A study on reform of public bureaucracy through governance (국가경영을 통한 관료제 개혁에 관한 연구)

  • Choi Rackin
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.3
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    • pp.211-218
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    • 2004
  • It was amazing that efficiency of bureaucratic system, when Marx Weber presented theory of bureaucracy. Now, Government and Bureaucratic organization are confronted with a forked road of change. The purpose of this paper is not so much to force choices among the alternative visions of governance but rather to make the choices available to governments more evident. Any choice of paradigms for government and administration is unlikely to be Pareto optimal, but we should be clear about what we receive and what we sacrifice when we make these judgements about governance. Today, government and public bureaucracy must be changed. There are needed an innovation of government and public bureaucracy. It must be changed concepts from government to governance. Governance is a national management.

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A MAC Parameter Optimization Scheme for IEEE 802.11e-based Multimedia Networks (IEEE 802.11e 기반 멀티미디어 네트워크를 위한 MAC 매개 변수 최적화 방법)

  • Sung, Min-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.2
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    • pp.455-461
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    • 2008
  • Enhanced Distributed Channel Access (EDCA) is a channel access scheme adopted by the IEEE 802.11e draft standard for QoS-enabled wireless local area networks. It classifies traffic into separate Access Categories (ACs) and achieves service differentiation by allowing each AC to have its own values of channel access parameters. This paper proposes a scheme to dynamically adapt the EDCA parameters to traffic environment so that they both maximize the throughput of non real-time traffics and meet the delay and throughput constraints of real-time traffics. For this purpose, we develop a design algorithm for efficient exploration of the EDCA parameter space. Using the algorithm, we derive a Pareto curve fur delay-throughput trade-off in each anticipated traffic environment. The Pareto database can then be used to optimally adjust the parameter according to the traffic environment and administrative policies. Simulation results show that compared with the default parameter configuration, the proposed scheme is better for delay, throughput guarantee and can improve the throughput of non real-time traffics by 12% on average.

Numerical Optimization of a Transonic Axial Compressor with Casing Grooves for Improvement of Operating Stability (케이싱 그루브가 장착된 천음속 축류압축기의 작동 안정성 향상을 위한 수치최적화)

  • Kim, Jin-Hyuk;Choi, Kwang-Jin;Kim, Kwang-Yong
    • The KSFM Journal of Fluid Machinery
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    • v.14 no.5
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    • pp.31-38
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    • 2011
  • Optimization using a hybrid multi-objective evolutionary algorithm coupled with response surface approximation has been performed to improve the performance of a transonic axial compressor with circumferential casing grooves. In order to optimize the operating stability and peak adiabatic efficiency of the compressor with circumferential casing grooves, tip clearance, angle distribution at blade tip and the depth of the circumferential casing grooves are selected as design variables. Three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model are discretized by finite volume approximations. The trade-off between two objectives with the interaction of blade and casing treatment is determined and discussed with respect to the representative clusters in the Pareto-optimal solutions compared to the axial compressor without the casing treatment.