• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.311-319
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• 2015

In this paper, in order to increase the production efficiency of the industrial plant, and predicts the resources of the manufacturing process, we have proposed a decision-making system for resource implementing the risk management effectively forecasting and risk management. A variety of information that occurs at each step efficiently difficult the creation of detailed process steps in the scenario you want to manage, is a frequent condition change of manufacturing facilities for the production of various products even within the same process. The data that is not contiguous products production cycle also not constant occurs, there is a problem that needs to check the variation in the small amount of data. In order to solve these problems, data centralized manufacturing processes, process resource prediction, risk prediction, through a process current status monitoring, must allow action immediately when a problem occurs. In this paper, the range of change in the design drawing, resource prediction, a process completion date using a regression algorithm to derive the formula, classification tree technique was proposed decision system in three stages through the boundary value analysis.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.5-17
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• 1996

There are various cases that we vote for making a decision or combining ideas (i.e. human being's opinions) in group meetings. Group Decision Support System(GDSS) provides us with a number of voting methods for decision making or aggregation of the ideas. It is generally difficult to select a voting method appropriate for given a meeting situation, without any aid of experts or computers having a knowledge on voting. In this paper we propose a supporting system for selecting an appropriate voting method. Since the selected method is recommended to the facilitator of GDSS, a part of time and effort related with the voting would be reduced. The knowledge in the system is represented as rules that are inductively generated from examples of voting. We used UNiK-INDUCE with ID3 algorithm so as to learn, which is a tool of developing expert systems.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.973-988
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• 2023

In real-life scenarios, we may have to deal with real numbers or numbers in intervals or a combination of both to solve multi-criteria decision-making (MCDM) problems. Also, we may come across a situation where we must combine this interval and actual number membership values into a single real number. The most significant factor in combining these membership values into a single value is by using aggregation operators or scoring algorithms. To overcome such a situation, we suggest the cubic hypersoft set (CHSS) concept as a workaround. Ultimately, this makes it simple for the decision-maker to obtain information without misconceptions. The primary aim of this study is to establish some operational laws for the cubic hypersoft set, present the fundamental properties of aggregation operators and propose an algorithm by using the technique of order of preference by similarity to the ideal solution (TOPSIS) technique based on correlation coefficients to analyze the stress-coping skills of workers.

• IE interfaces
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• v.21 no.4
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• pp.444-455
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• 2008

In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.30-33
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• 2016

With the advent of big data, data mining is more increasingly utilized in various decision-making fields by extracting hidden and meaningful information from large amounts of data. Even as exponential increase of the request of unrevealing the hidden meaning behind data, it becomes more and more important to decide to select which data mining algorithm and how to use it. There are several mainly used data mining algorithms in biology and clinics highlighted; Logistic regression, Neural networks, Supportvector machine, and variety of statistical techniques. In this paper it is attempted to compare the classification performance of an exemplary algorithm J48 and REPTree of ML algorithms. It is confirmed that more accurate classification algorithm is provided by the performance comparison results. More accurate prediction is possible with the algorithm for the goal of experiment. Based on this, it is expected to be relatively difficult visually detailed classification and distinction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.545-552
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• 2006

The purpose of this study is to develop an optimal, long-term planning model for improvement of water distribution networks. The water distribution system is divided into sub-zones and the decision of improvement plan is made for each sub-zone. Costs for replacement, rehabilitation and repair, benefits including reduced pumping and leakage costs, and hydraulic reliability are considered to make optimal decision for improvement planning of water network. Harmony search algorithm is applied to optimize the system and hydraulic analysis model EPANET is interfaced with the optimal decision model to check the hydraulic reliability, The developed model is applied to actual water distribution system in Daegu-city, South Korea. The new model which use durability, conveyance and cost as a decision variable is different from existing methods which use only burying period and pipe type and can be used as optimal decision making system for water distribution network.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.323-328
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• 2005

Bridge structures are properly designed in accordance with the design specifications with required safety margin. However, due to the heavy vehicle traffic and environmental attacks, bridge often requires repairs and the deteriorated one should be replaced or rehabilitated. In this paper, a prior ranking algorithm is proposed to assist a decision making process in bridge management at network level. Based on the literature survey for the existing studuies, two important factors which affect the decision making procedure for bridge management at network level are identified. These factors are implemented into the algorithm as a load carrying capacity function and traffic function, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5449-5464
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• 2018

Recent works have validated the possibility of reducing the energy consumption in wireless heterogeneous networks, achieved by switching on/off some base stations (BSs) dynamically. In this paper, to realize energy conservation, the discrete time Markov Decision Process (DTMDP) is developed to match up the BS switching operations with the traffic load variations. Then, an asynchronous decision-making algorithm, which is based on the Bellman equation and the on/off priorities of the BSs, is firstly put forward and proved to be optimal in this paper. Through reducing the state and action space during one decision, the proposed asynchronous algorithm can avoid the "curse of dimensionality" occurred in DTMDP frequently. Finally, numerical simulations are conducted to validate the effectiveness and advantages of the proposed asynchronous on/off strategies.