• 농촌지도와개발
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• 제16권4호
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• pp.939-965
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• 2009

The Machine Learning has been identified as a promising approach to knowledge-based system development. This study aims to examine the ability of machine learning techniques for farmer's decision making and to develop the reference model for using pig farm data. We compared five machine learning techniques: logistic regression, decision tree, artificial neural network, k-nearest neighbor, and ensemble. All models are well performed to predict the sow's productivity in all parity, showing over 87.6% predictability. The model predictability of total litter size are highest at 91.3% in third parity and decreasing as parity increases. The ensemble is well performed to predict the sow's productivity. The neural network and logistic regression is excellent classifier for all parity. The decision tree and the k-nearest neighbor was not good classifier for all parity. Performance of models varies over models used, showing up to 104% difference in lift values. Artificial Neural network and ensemble models have resulted in highest lift values implying best performance among models.

• 감성과학
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• 제10권1호
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• pp.23-36
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• 2007

본 연구는 소비자가 모바일 기기를 구매함에 있어서 어떤 멘탈 모델을 가지고 있는지를 파악하는데 중점을 두고 멘탈 모델의 추출과 분석을 시도하였다. 본 연구는 모바일 기기 구매 의사결정 과정에서 IT 친숙도에 따라 서로 다른 멘탈 모델을 가지고 있을 것이라는 가설을 가지고 크게 두 부분으로 나누어 연구를 진행하여 인지 과제 분석 방법의 하나인 Critical Decision Method를 이용하여 멘탈 모델을 이루는 27가지 구성요소들을 추출하였고, 이렇게 추출된 구성요소들을 바탕으로 IT 친숙도에 따라 소비자의 멘탈 모델을 두 그룹으로 구분하여 Pathfinder 알고리즘과Social Network Analysis를 이용하여 각각의 멘탈 모델을 분석하고 있다. 분석결과 IT 친숙도가 높은 그룹은 멘탈 모델을 구성하는 요소들이 각각의 독자적 특성에 따라 구매 의사결정 과정에서 비교적 조직적이고 분명하게 구분된 역할을 수행하는 것으로 나타난 반면, IT 친숙도가 낮은 그룹은 멘탈 모델 구성 요소들 간의 관계나 역할이 불분명하고 혼재된 경향을 보였으며 구매 의사결정 과정에서 외부 의견이나 사회적 통념을 중시하는 것으로 나타났다.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 추계학술대회
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• pp.199-207
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• 2010

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. In this paper, we use the analytic hierarchy process in weights calculating. For the purpose of making optimal decision, the data of three different smart phones models are used.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.1114-1116
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• 2005

Shop floor control systems (SFCS) are used to make real-time planning and scheduling decisions to optimize the efficiency of manufacturing shops. These shops exhibit a non-linear, dynamic evolution caused by 1) the concurrent flows of disparate parts following complex routings, 2) a variety of machines that breakdown at random times, 3) stochastic arrivals of new parts with different priorities, and 4) jobs that have probabilistic processing times and transportation times. Because of their ability to capture that evolution faithfully, simulation models are often used in the aforementioned decisions. In this paper, various types of decision-making problems encountered in a shop floor have been investigated and categorized into process related problems and resource related problems for shop floor simulation.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.734-741
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• 2002

The importance of efficient Supply Chain Management is increasing in accordance with recent industrial environment, such as globalization of business, complexity and diversity of company's management structure, and variety of customer's demand. In a rapidly changed environment of business, quick and efficient decision making is the important matter to the survival of the company. The purpose of this study supports decision making for efficient supply chain management. In this study, we consider simultaneously and mutually reflecting the preference of each constituent (Supplier, Manufacturing plant, Distribution center, Customer) on supply chain network, and decide company's strategic choice and coordinated production/distribution models of company. The Analytical Hierarchy Process is used for decision making of qualitative and quantitative elements. We use the results of AHP as inputs and propose mathematical models thru Mixed Integer Programming.

• 산업경영시스템학회지
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• 제21권45호
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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.

• 기술혁신학회지
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• 제6권2호
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• pp.159-174
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• 2003

This study reviews the emerging new model of science and technology decision making process. It examines the open source software development model and community-based innovation model in technological innovation and the active participation model of Consensus Conference and Citizen's Jury in science and technology policy decision making. It argues that the role and influence of users in innovation and policy making is becoming important in these emerging models and the existing supplier-led, bureaucratic model of science and technology decision making model is changing.

• 가정과삶의질연구
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• 제4권2호
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• pp.89-101
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• 1986

This study sought to investigate the presence and characteristics of postulated variables(involvement & empathy) that may moderate the need for overt conflict - resolving behavior when husbands and wives disagree on a certain purchasing subdecision and that may explain husband - wife decision - making patterns. For the above purpose, the analyses of this study are based on response of 180 husbands and wives(90 couples) to questions concerning 11 subdecisions of house and sofa-set purchasing decisions. The results are summarized as follows; 1) Income, education, and wives job do not significantly differenciate the levels of involvement and empathy except that education does the levels of wives involvement and empathy and that wives job does the levels of husbands involvement. 2) Husbands and wives indicate significantly different levels of involvement and empathy on most subdecisions. i. e., wives regard all subdecisions importantly. and on 3 subdecisions of joint decision - making pattern, they have the higher consideration for their husband's preferences. 3) Incongruency in husband - wife responses to the questions of decision - making patterns are moderate. 4) Husbands and wives involvement / empathy discriminate well the patterns of decision - making on various subdecisions within 2 product classes. Wives empathy accounts for much discriminating power in both instances. Thus, the need to add these involvement and empathy variables to models of family decision - making is sugguested.

• 가정과삶의질연구
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• 제23권3호
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• pp.77-91
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• 2005

This study conceptualized the factors affecting college students' consumer decision-making styles from the perspective of consumer socialization. A number of antecedent variables identified by preceding studies (age, gender, place where one grew up, job experience, main reason for working, amount of allowance, family income, socio-economic status) and socialization agents such as family, peers, mass media were included in the analysis. This study extends previous studies by examining a theoretical link between the antecedent variables and socialization agents. Three hundred and forty one undergraduate students in Daejeon were participated in this study. Stepwise multiple regression md path analysis were conducted. The results of this study are as follows: 1. Six consumer decision-making styles were identified. 2. The influence of the socialization agents, especially mass media and several antecedent variables, especially gender and main reason for working, played important roles in consumer decision-making styles. 3. Several antecedent variables, especially gender and family income, were related only with the influence of socialization agents. 4. Six path-analysis models that illustrate the relationships among the antecedent variables, the socialization agents and consumer decision-making styles were proposed.

• Journal of Computing Science and Engineering
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• 제2권2호
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• pp.200-219
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• 2008

The effective management of uncertainty is one of the most fundamental problems in medical decision making. According to the literatures review, most medical decision models rely on point estimates for input parameters. However, it is natural that they should be interested in the relationship between changes in those values and subsequent changes in model output. Therefore, the purpose of this study is to identify the ranges of numerical values for which each option will be most efficient with respect to the input parameters. The Nonhomogeneous Poisson Process(NHPP) was used for describing the behavior of aging chronic diseases. Three kind of failure models (linear, exponential, and power law) were considered, and each of these failure models was studied under the assumptions of unknown scale factor and known aging rate, known scale factor and unknown aging rate, and unknown scale factor and unknown aging rate, respectively. In addition, this study illustrated developed method with an analysis of data from a trial of immunotherapy in the treatment of chronic Granulomatous disease. Finally, the proposed design of Bayesian value of information analysis facilitates the effective use of the computing capability of computers and provides a systematic way to integrate the expert's opinions and the sampling information which will furnish decision makers with valuable support for quality medical decision making.