• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.7-21
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• 2024

There are various machine learning techniques such as Reinforcement Learning, Deep Learning, Neural Network Learning, and so on. In recent, Large Language Models (LLMs) are popularly used for Generative AI based on Reinforcement Learning. It makes decisions with the most optimal rewards through the fine tuning process in a particular situation. Unfortunately, LLMs can not provide any explanation for how they reach the goal because the training is based on learning of black-box AI. Reinforcement Learning as black-box AI is based on graph-evolving structure for deriving enhanced solution through adjustment by human feedback or reinforced data. In this research, for mutually exclusive decision-making, Mutually Exclusive Learning (MEL) is proposed to provide explanations of the chosen goals that are achieved by a decision on both ends with specified conditions. In MEL, decision-making process is based on the tree-based structure that can provide processes of pruning branches that are used as explanations of how to achieve the goals. The goal can be reached by trade-off among mutually exclusive alternatives according to the specific contextual conditions. Therefore, the tree-based structure is adopted to provide feasible solutions with the explanations based on the pruning branches. The sequence of pruning processes can be used to provide the explanations of the inferences and ways to reach the goals, as Explainable AI (XAI). The learning process is based on the pruning branches according to the multi-dimensional contextual conditions. To deep-dive the search, they are composed of time window to determine the temporal perspective, depth of phases for lookahead and decision criteria to prune branches. The goal depends on the policy of the pruning branches, which can be dynamically changed by configured situation with the specific multi-dimensional contextual conditions at a particular moment. The explanation is represented by the chosen episode among the decision alternatives according to configured situations. In this research, MEL adopts the tree-based learning model to provide explanation for the goal derived with specific conditions. Therefore, as an example of mutually exclusive problems, employment process is proposed to demonstrate the decision-making process of how to reach the goal and explanation by the pruning branches. Finally, further study is discussed to verify the effectiveness of MEL with experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.81-91
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• 1978

Decision models are an attempt to reduce uncertainty in the decision making process. The models describe the relationships of variables and given proper input data generate solutions to managerial problems. These solutions may not be answers to the problems for one of two reasons. First, the data input into the model may not be consistant with the underlying assumptions of the model being used. Frequently parameters are assumed to be deterministic when in fact they are probabilistic in nature. The second failure is that often the decision maker recognizes that the data available are not appropriate for the model being used and begins to collect the required data. By the time these data has been compiled the solution is no longer an answer to the problem. This relates to the timeliness of decision making. The authors point out throught the use of an illustrative problem that stocastic models are well developed and that they do not suffer from any lack of mathematical exactiness. The primary problem is that generally accepted procedures for data generation are historical in nature and not relevant for probabilistic decision models. The authors advocate that management information system designers and accountants must become more familiar with these decision models and the input data required for their effective implementation. This will provide these professionals with the background necessary to generate data in a form that makes it relevant and timely for the decision making process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.89-98
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• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.69-78
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• 2007

In real world, the project managers handle conflicting goals that govern the use of resources within the stipulated time and budget with required quality and safety. These conflicting goals are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The fuzzy linear programming model proposed herein helps project managers to minimize total project costs, completion time, and crashing costs considering indirect costs, contractual penalty costs etc by practically charging them in terms of direct cost of the project. A case study of bituminous pavement under construction is considered to demonstrate the feasibility of applying the proposed model for optimization of project parameters. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with multiple fuzzy goal values. Additionally, the proposed model provides a systematic decision-making framework, enabling decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model with other models include, flexible decision-making process, multiple objective functions, and wide-ranging decision information.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.

• Journal of Digital Convergence
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• v.8 no.1
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• pp.55-69
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• 2010

This thesis looks closely at the moderating effect of individual variables while we analyzed how corporate's ethics policies have influence on his ethical decision-making behaviors. The subjects of the research were full-time employees (n=211) in the Seoul metropolitan region. The research model was substantiated through statistical analysis of credibility and validity, correlation, variance, and moderated regression analysis (MRA). This study found that within an organization with a code of ethics, the level of enforcement of the code and the level of employee awareness of core values sought by the company determined the level of influence of the code on ethical decision making. In other words, internal factors exerted a greater influence than external evaluation of a corporation's ethical decision making practices and therefore, it is necessary for decision-making practices to be transparent and recognized by the members within an organization. The study also found that the employee's awareness about the long-term visions of the company at a higher level and the employees who have a locus of control to their members internally acted as independent variables as well as control variables on the ethical decision-making. In addition, there were great differences in the level of ethical decision-making among the variables used as controls, which means these differences were related to the individual variables. Accordingly, in order to get ethical decision-making practices at a higher level, a education & training program will be designed and implemented variously as considering on the particular characteristics of the control variables we used in this study.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.2
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• pp.81-90
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• 2013

A study on the flow-structure characteristics of marine 3/2WAY pneumatic valve is essential for optimizing the performance of ship engines. It is important that the valve has desirable safety factor and reduced weight from safety and economic point of view. In this paper, flow-structure characteristics of pneumatic valve is obtained by being optimized based on the proper design criteria. The air with the pressure of 30 bar is the working fluid which is made to fill in the tack in short time. This time is defined as the filling time. On optimum design by considering the flow-structure characteristics, the approach is based on (1) the mathematical formulation of design decisions using the compromise decision-making method, and (2) the approximation technique of response surfaces. The methodology is demonstrated as the multi-objective optimization tool to improve the performance of marine 3/2WAY pneumatic valve.

• Korean Management Science Review
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• v.11 no.2
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• pp.185-206
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• 1994

This paper investigated, using a flexible approach, the effects of the psychological type of the decision maker and the advanced format of information presentation on decision maker performance in a computer-simulated production game. The current sutdy was guided by a model derived from a general model developed by Chervany, Dickson, and Kozar(1972). The experimental model had two dependent variables; total profit and decision making time. Three independent variables representing the psychological type of the decision maker, the report format, and decision aids were used in this study.

• Journal of the Korean Home Economics Association
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• v.48 no.4
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• pp.83-102
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• 2010

This paper investigates whether intra-household bargaining power affects couples' caregiving decisions during instances of competing parental demands for assistance. The primary focus is on examining how partners' bargaining power influences the relative allocation of time resources between parents and parents-in-law, assuming that children prefer to transfer caregiving resources toward their own parents over their parents-in-law. The findings in this study reject the bargaining theory that couple's parental care behavior results from a bargaining process between the husband and the wife. More specifically, the results did not clearly show that children prefer to transfer caregiving resources toward their own parents over their parents-in-law. Decision-making power, measured by final decision-making authority, also failed to affect the relative care transfers.

• Journal of Home Health Care Nursing
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• v.17 no.1
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• pp.21-27
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• 2010

Purpose: The study evaluated a program to shorten EMC stay time. Methods: The subjects were EMC patients, and comprised a control group of 8,477 and an experimental group of 8,378. Data were collected from June 2006 to August 2007, and analyzed concerning stay time for doctor visit, decision making, and discharge. The data were analyzed by $X^2$-test and ANCOVA using SPSS14.0. Result: The stay time of doctor visit, decision making and discharge of the experimental group was significantly less compared to the control group. Using second and third grade triage criteria, the stay time of experimental group was statistically reduced from the control. Conclusion: The implemented shortening program was effective in reducing EMC stay time and increasing EMC effectiveness.