• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.4
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• pp.10-18
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• 2002

Network topology design is a multiobjective problem with various design components. The components such as cost, message delay and reliability are important to gain the best performance. Recently, Genetic Algorithms(GAs) have been widely used as an optimization method for real-world problems such as combinatorial optimization, network topology design, and so on. This paper proposed a method of Multi-objective GA for Design of the network topology which is to minimize connection cost and message delay time. A common difficulty in multiobjective optimization is the existence of an objective conflict. We used the prufer number and cluster string for encoding, parato elimination method and niche-formation method for the fitness sharing method, and reformation elitism for the prevention of pre-convergence. From the simulation, the proposed method shows that the better candidates of network architecture can be found.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.247-255
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• 2004

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.763-765
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• 2015

The study is being conducted to ensure the transparency of research and development have identified the problems of the current system and improve the way out. Such a study about the subject that do not follow either outside the institutional system has a disadvantage compared to an unfulfilled. R & D in order to prevent the misuse and fraud enforcement shall detect abnormal transactions that occur from transactions between research institutions and credit card issuers in real time. In this paper, we propose a detection method for real-time transaction over. It is able to detect and respond fraudulent transactions that may occur in a variety of environments by adding the data obtained by the business rules to derive stopped making detection system.

• Korean journal of applied entomology
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• v.50 no.4
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• pp.383-393
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• 2011

Because communication facilitates behaviors that are critical for survival and reproduction, it is central to the study of behavior and evolution. One of the most important and difficult issues with respect to communication has been the definition of communication itself. Broadly, it can be defined as an exchange of information from a signaler to a receiver. However, evolution of a signal is likely possible only under conditions in which both the signaler and receiver increase fitness from the exchange of information, often referred to as "true communication." The three primary sensory channels of communication used by animals are chemical, visual, and acoustic. Chemical signals are the oldest and most widespread method of communication. Visual and acoustic signals convey a great deal of information due to ease of modulation, flexibility of signal production, and fast transmission. The most widespread contexts in which animals communicate are sexual interaction and conflict resolution. Signals used for sexual interaction typically contain information about species identity and sexual attractiveness, whereas signals used for conflict resolution may contain information about resource holding potential. Other contexts under which animals communicate include territorial defense, parent-offspring interactions, social integration, sharing of environmental information, and auto-communication.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1569-1580
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• 2004

One commonly used approach to deal with uncertainty is Bayesian network which represents joint probability distributions of domain. There are some attempts to team the structure of Bayesian networks automatically and recently many researchers design structures of Bayesian network using evolutionary algorithm. However, most of them use the only one fittest solution in the last generation. Because it is difficult to combine all the important factors into a single evaluation function, the best solution is often biased and less adaptive. In this paper, we present a method of generating diverse Bayesian network structures through fitness sharing and combining them by Bayesian method for adaptive inference. In order to evaluate performance, we conduct experiments on learning Bayesian networks with artificially generated data from ASIA and ALARM networks. According to the experiments with diverse conditions, the proposed method provides with better robustness and adaptation for handling uncertainty.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• The Korean Journal of Elementary Counseling
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• v.11 no.2
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• pp.153-169
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• 2012

The purpose of this study is to investigate the most rational method of grouping peers to understand the impact of peer relationship on individual development of elementary school students. For the study, students at a class of the 3rd year(male) and a class of the 4th(female) year at elementary schools in Busan and Ulsan were surveyed to see the differences between various methods of classification of peer relation subgroup on the basis of cooccurence of perception data and psychological preference data. Two questionnaires were used; a questionnaire of perception and a questionnaire of psychological preference. With the perception data, value of sharing relationship was applied to classify peer relation subgroup and with the psychological preference data, interest relationship was expanded to classify peer relation subgroup of more than third party relationship. The result of this study showed that in the case of girls, there was high congruency between the classifications of peer relation subgroup by perception data and by preference data, whereas in the case of boys, there was difference between the classifications of peer relation subgroup by perception data and by preference data, which implies that boys can form a peer group even if there is psychological difference among members but girls can form a peer group only when there is psychological preference among them. Such a result shows that there is difference between boys and girls in the process of forming peer relationship. It is suggested that comparison of fitness be made between classification of peer relation subgroup by a homeroom teacher, by perception data and by psychological preference for rational classification of peer relationship among male children.

• Korean Journal of Environment and Ecology
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• v.29 no.5
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• pp.681-692
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• 2015

It is well documented that physiological and nutritional condition of wintering birds is strongly related to migration success to breeding sites, and also breeding success. However, how abiotic factors during winter affect the migration and breeding successes still remains unclear. Thus, this study developed a dynamic-state-dependent model for wintering life-history to identify the potential impact on the life-history, success to breeding site and breeding success of wintering birds, which are related to temperature fluctuation, interspecific competition and human disturbance at the wintering sites. To find the best-fit-model, we referred to the existing research data on wintering ecology of Red-crowned cranes (Grus japonensis) in Cheolwon, Korea, which is well documented as a long-term wintering study. Our model predicted that the higher temperature fluctuation and a higher rate of human disturbance are negatively related to migration success to breeding sites and their fitness, ultimately breeding success via changing of proportion in resource allocation (for e. g., lower energy compensation or higher level of stress accumulation). Particularly, the rate of body mass compensation after arrival at wintering sites may be accelerated when there are less temperature fluctuations and a lower rate of human disturbance. In addition, the rate of interspecific competition sharing the wintering foraging sites is negatively related to the rate of body mass compensation. Consequently, we discussed the conservation strategies of wintering birds based on the outcomes of the model.