• Title/Summary/Keyword: Statistical Decision Making

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Estimation of Income Distribution for Domestic Grape-producing Farms Based on the Subjective Simulation Process (주관적 모의실험을 기반으로 한 국내 포도농가의 소득 분포 추정)

  • Koo, Seung-Mo
    • Korean Journal of Agricultural Science
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    • v.37 no.2
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    • pp.315-321
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    • 2010
  • Decision-makings or the related policies regarding domestic grape production heavily depends upon the known market price data and official statistics periodically announced by government, at national level. However, usual adaption of the 'simple means' from these data may bring seriously biased decision-makings when the original data are biased, especially when the data are not convinced to be normal distributions to decision makers. In this regards, this study employs Monte Carlo simulation technique to overcome the limitations, based on the decision makers' subjective assumptions on the known data, and, tries to come up with flexible range of business information regarding grape-producing farm income. The approach used in this study also provides possibility that it may be useful when adapting subjective assumptions from various statistical distributions.

Changes in Statistical Knowledge and Experience of Data-driven Decision-making of Pre-service Teachers who Participated in Data Analysis Projects (데이터 분석 프로젝트 참여한 예비 교사의 통계적 지식에 대한 변화와 데이터 기반 의사 결정의 경험)

  • Suh, Heejoo;Han, Sunyoung
    • Communications of Mathematical Education
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    • v.35 no.2
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    • pp.153-172
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    • 2021
  • Various competencies such as critical thinking, systems thinking, problem solving competence, communication skill, and data literacy are likely to be required in the 4th industrial revolution. The competency regarding data literacy is one of those competencies. To nurture citizens who will live in the future, it is timely to consider research on teacher education for supporting teachers' development of statistical thinking as well as statistical knowledge. Therefore, in this study we developed and implemented a data analysis project for pre-service teachers to understand their changes in statistical knowledge in addition to their experiences of data-driven decision making process that required them utilizing their statistical thinking. We used a mixed method (i.e., sequential explanatory design) research to analyze the quantitative and qualitative data collected. The findings indicated that pre-service teachers have low knowledge level of their understanding on the relationship between population means and sample means, and estimation of the population mean and its interpretation. When it comes to the data-driven decision making process, we found that the pre-service teachers' experiences varied even when they worked as a small group for the project. We end this paper by presenting implications of the study for the fields of teacher education and statistics education.

AHP-based Technology Start-ups Factors Analysis System (AHP에 기반을 둔 기술창업 요인 분석 시스템)

  • Joun, Hyang-Soon;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.13 no.4
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    • pp.311-317
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    • 2015
  • It is important to analyze and offer specialized start-ups effect factors for collegians in order to systematically and successfully support technology-centered start-ups of collegians, whose social experience is insufficient. However, consistently changing start ups environmental analysis is difficult, which can be a problem, because technology-centered start-ups factor analysis is carried out depending on statistical package. This paper proposes an ATSA system that demonstrates effect factors on technology-centered start-ups decision making as a hierarchial structure by using AHP, inputs the effect factors to judgment matrix after pre-processing, calculates standardized values and weights, verifies consistency, and draws priorities through weights integration. It was confirmed that the ATSA system can efficiently support decision making for technology-centered start-ups by quantitatively analyzing qualitative factors through experiments by applying multi-criteria decision making to the analyses of start-ups founders' internal and external factors and various start-ups environments.

Regulatory Aspect of Risk Assessment and Management

  • Lee, Hyomin;EunkyungYoon;Jeeyeun Han
    • Toxicological Research
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    • v.17
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    • pp.17-24
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    • 2001
  • Risk assessment is useful tool making good decisions on the risks of certain hazardous com-pound and suggests safe margin through scientific process using toxicological data, statistical tool, exposure value and relevant variants. The goal of risk management is to protect the public health from hazardous compound based on result of risk assessment having reality. For the suggestion of exact man-aging information, risk assessment must be designed to represent a "plausible estimate" of the exposure to the individuals and to minimize uncertainty. Risk assessment methodology and knowledge are expected to change more rapidly than before and up-to-date methodology should be applied in regulatory aspects through the Agency. For the useful application of risk assessment, the communication between the risk assessor and the risk manager is needed before the initiation of the risk assessment and upon its completion. Generally, the risk assessment itself as a practical tool in the regulatory decision making process would be regarded with social economic impact.ic impact.

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Baseline Study to Develop a Consumer Information System (소비자정보시스템 구축을 위한 기반 연구)

  • Nam Su-Jung;Kim Kee-Ok
    • Journal of Families and Better Life
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    • v.23 no.1 s.73
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    • pp.125-137
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    • 2005
  • Information technology is an important driving force that has changed consumer information environments. In order to adjust in the new environments, consumers need an innovative information system. The purpose of this study was to develop a Consumer Information System (CIS). CIS is a device that supports consumer's decision-making process and elevates consumer information competence. The CIS was constructed by the following steps: (1) organization of developers, (2) systematization of consumer information, (3) data loading, (4) integration of consumer database: data warehouse, (5) data distribution, (6) composition of data mart, (7) use of data access tools: data-mining, OLAP, statistical analysis, Q+R, (8) data visualization: web server.

A Study on the Self-Evolving Expert System using Neural Network and Fuzzy Rule Extraction (인공신경망과 퍼지규칙 추출을 이용한 상황적응적 전문가시스템 구축에 관한 연구)

  • 이건창;김진성
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.231-240
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    • 2001
  • Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

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A Study of Factors Influencing Delivery Methods Selection on Public Construction Projects (공공공사 발주방식 선정에 영향을 미치는 요인 연구)

  • Kim, Dae-gil;Lee, Ung-Kyun;Lee, Hak-Joo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2014.11a
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    • pp.218-219
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    • 2014
  • The selection of an appropriate contract method is vital for the successful operation of the project. However, there has been a lack of studies on objective decision making support models for use in the planning stage of a project contract. The present study had the goal of analyzing the factors that influence contract method selection, as an initial study for developing a project contract method selection model. The existing related studies were analyzed, and the factors considered in the literature were selected. Then, based on the findings, the opinions of an expert group on the important factors for contract method selection were collected through a survey. The collected opinions were analyzed using factor analysis, a statistical analysis method. The results will be utilized in the future as preliminary data for developing a decision making model for selecting a contract method.

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Deciding the Optimal Shutdown Time Incorporating the Accident Forecasting Model (원자력 발전소 사고 예측 모형과 병합한 최적 운행중지 결정 모형)

  • Yang, Hee Joong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.4
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    • pp.171-178
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    • 2018
  • Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

Channel Statistical MAC Protocol for Cognitive Radio

  • Xiang, Gao;Zhu, Wenmin;Park, Hyung-Kun
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.40-44
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    • 2010
  • opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. A dynamical sensing range as a important parameter introduced to maintain the our protocol performance. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.

Multi-Channel MAC Protocol Using Statistical Channel Utilization for Cognitive Networks

  • Xiang, Gao;Zhu, Wen-Min;Park, Hyung-Kun
    • Journal of information and communication convergence engineering
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    • v.8 no.3
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    • pp.273-276
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    • 2010
  • Opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.