• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• 디지털융복합연구
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• 제14권3호
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• pp.209-217
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• 2016

최근 경제성장과 더불어 삶의 질이 향상됨에 따라 야외활동이 증가되었으며, 야외활동의 진행여부 의사결정은 기상여건과 밀접한 관계를 갖고 있다. 현재 이러한 야외활동 의사결정은 기상청의 일기예보와 주관적인 경험에 의해 결정되어지고 있다. 따라서, 야외활동 의사결정을 위해 기상정보를 기반으로 객관적 근거를 제시할 수 있는 분석 방법이 필요하다. 논문에서는 데이터마이닝을 기반으로 기상정보를 분석하여 야외활동 의사결정을 지원할 수 있는 기상정보 분석 알고리즘을 제안한다. 또한, 프로야구 일정 히스토리와 자동기상관측장비의 관측 자료를 데이터마이닝의 분류 알고리즘을 적용하여 실험을 수행하고, 제안한 알고리즘의 향상된 성능을 검증하였다.

• 한국수자원학회논문집
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• 제41권2호
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• pp.127-135
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• 2008

하수관거 개량사업의 주된 목적은 Inflow/Infiltration (I/I)를 제거 및 통수능력 확보이다. 최근 노후 하수관거의 개 보수 및 신설 사업이 활발히 이루어지고 있으나 현재의 사업들은 관거 데이터의 부족, 유량 및 수질 자료의 장기적인 측정 미비 등으로 인하여 효율적인 사업을 진행시키기에 무리가 있다. 본 연구에서는 하수관거 개량사업을 보다 효율적으로 진행시키기 위하여 Rehabilitation Weighting Model (RWM)과 Rehabilitation Priority Model (RPM)로 구성된 의사결정모형을 개발하였다. RWM은 시간 및 예산상의 제약으로 인하여 주요 지점에서만 관측되는 I/I를 상류의 각 관거별로 I/I를 산정하며, 관거별 I/I는 Analytic Hierarchy Process (AHP)를 통하여 산정된 8개 결함항목별 가중치에 따라서 결정된다. RPM은 Genetic Algorithm (GA)를 이용하여 소유역별 최적개량우선순위를 산정한다. 이것은 공사 기간 중 발생하는 I/I를 최소화시키기 위한 소유역별 공사 순서를 설정함으로써 하수처리장의 처리비용을 절감시킴으로써 하수관거 개량사업의 효율적인 시행을 위한 판단 기준을 제시해준다.

• 산업경영시스템학회지
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• 제40권4호
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• 한국통신학회논문지
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• 제18권6호
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• pp.824-834
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• 1993

주파수 이용 효율을 극대화하기 위한 셀룰러 이동 통신 시스템에서는 셀의 반경이 작아지면 이동국이 한 셀내에 잔류하는 시간이 짧아지고, 많은 핸드오버가 발생할 수 있게 된다. 또한 핸드오버 결정에 사용되는 수신 신호 전계 강도와 비트 에러율, 기지국과 이동국과의 거리 등의 파라미터는 부정확하게 측정되고 단일 파라메터에 의해 핸드오버 결정은 불충분하기 때문에, 측정치들을 함께 고려하여 핸드오버 결정을 강인하고 유연하게 할 수 있는 알고리즘을 필요로 한다. 본 논문에서는 퍼지 이론을 이용한 다기준(multi-criteria) 의사 결정 문제로 부정확한 다수의 파라미터를 이용하는 핸드오버 알고리즘을 제안하였는데 모의 실험 결과에 따르면 이 알고리즘을 쓸 경우 전체적인 의사 결정이 신뢰성이 있으며 유연하게 되었다. 제안된 알고리즘은 호 중단율, 핸드오버 요청율등의 평가 파라미터를 이용하여 전계 강도만을 이용하는 방법들과 비교되었다.

• 한국기계가공학회지
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• 제15권5호
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• pp.39-47
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• 2016

Nowadays, several welding processes are generally used to join parts together, and the materials are generally steel, aluminum, copper, stainless steel, and other difficult-to-weld materials. If a proper welding process is chosen, it is helpful for welding parts. However, there is no desirable technique for appropriately deciding on the welding process in the industry. Therefore, an appropriate method of selecting a welding process is needed for the novice worker in the industry. In this sense, a new analytic network process (ANP) technique is used for effective decision making in welding. By considering several criteria in ANP, a selection method is suggested to decide on the proper welding process. In the study, several criteria were considered for the proper welding of parts. By considering a matrix of prior interdependence effects among various welding processes, a decision-making method based on an ANP is accomplished using a weighting matrix, which is supposed to select an appropriate welding process. In addition, for appropriate decision criteria of the welding process, several factors, such as material, shape, precision, economics, and equipment, are used to accomplish the ANP algorithm. Moreover, the final weighting matrix is calculated following its ANP strategy. Furthermore, this decision-making technique is applied to both stainless razor spot joining and thick steel pipe joining. The results show its reliability and practicality, and the novice engineer and manager can use this technique to determine the best welding process.

• International Journal of Contents
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• 제17권4호
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• pp.79-90
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• 2021

With the deepening of population aging, pension has become an urgent problem in most countries. Community smart pension can effectively resolve the problem of traditional pension, as well as meet the personalized and multi-level needs of the elderly. To predict the pension intention of the elderly in the community more accurately, this paper uses the decision tree classification method to classify the pension data. After missing value processing, normalization, discretization and data specification, the discretized sample data set is obtained. Then, by comparing the information gain and information gain rate of sample data features, the feature ranking is determined, and the C4.5 decision tree model is established. The model performs well in accuracy, precision, recall, AUC and other indicators under the condition of 10-fold cross-validation, and the precision was 89.5%, which can provide the certain basis for government decision-making.

• 한국군사과학기술학회지
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• 제23권4호
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• pp.381-388
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• 2020

Weapon target assignment problem is an essential technology for automating the operator's rapid decision-making support in a battlefield situation. Weapon target assignment problem is a kind of the optimization problem that can build up an objective function by maximizing the number of threat target destructed or maximizing the survival rate of the protected assets. Weapon target assignment problem is known as the NP-Complete, and various studies have been conducted on it. Among them, a greedy heuristic algorithm which guarantees (1-1/e) approximation has been considered a very practical method in order to enhance the applicability of the real weapon system. In this paper, we formulated the weapon target assignment problem for supporting decision-making at the level of artillery. The lazy strategy based on hierarchical structure is proposed to accelerate the greedy algorithm. By experimental results, we show that our algorithm is more efficient in processing time and support the same level of the objective function value with the basic greedy algorithm.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 춘계학술대회
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• pp.283-291
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• 2005

The development of mobile applications is fast in recent years. However, nearly all applications are for messaging, financial, locating services based on simple interactions with mobile users because of the limited screen size, narrow network bandwidth, and low computing power. Processing an algorithm for supporting a group decision process on mobile devices becomes impossible. In this paper, we introduce the mobile-oriented simple interactive procedure for support a group decision making process. The interactive procedure is developed for multiple objective linear programming problems to help the group select a compromising solution in the mobile Internet environment. Our procedure lessens the burden of group decision makers, which is one of necessary conditions of the mobile environment. Only the partial weak order preferences of variables and objectives from group decision makers are enough for searching the best compromising solution. The methodology is designed to avoid any assumption about the shape or existence of the decision makers's utility function. For the purpose of the experimental study of the procedure, we developed a group decision support system in the mobile Internet environment, MOBIGSS　and applied to an allocation problem of investor assets.

• 산업경영시스템학회지
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• 제26권2호
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• pp.1-8
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• 2003

The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.