• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.4
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• pp.65-71
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• 2004

Stress Path Search Model of Evolutionary Structural Successive Optimization (SPSMESO) using Triangular Irregular Network(TIN) was developed for improving over burden at initial design of ESO and strict stress direction of strut-and-tie model and truss model. TIN was applied for discretizing structures in flexible stress path and segments of TIN was analyzed as one-dimensional line element for calculating stress. Finally, stress path was searched using ESO algorithm. SPSMESO was efficient to express the direction of stress for 2D structure and time saving.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.37-46
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• 2007

In designing the structure, the stress path is the basic data. But the stress path is not standardized to analysis the structure. So the one-dimensional frame element structure model with the triangle irregular network is used to solve the problem. And the refined evolutionary structural optimization(RESO) used in structural topology optimization is applied to this study. Through this process, the search method of the stress path is advanced and the burden of the calculation. is reduced.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.113-127
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• 1993

In this study, a substitution model of the evolutionary generations of technological products is presented. The purpose of the model is to examine the demand side mechanisms which generate successive product life cycles along the path of technological improvements. In the model, the nature of substitution processes is summarized dto the demand function which is derived from the consumer's udtility maximization problem. To describe the nature of technological substitution processes, the concept of the vertical differentiation and the consumption externalities are considered in the utility function. The former is used to characterize the result of technological improvement and the latter is used in explaining the inertia of demand. To show the validity of the model, an empirical study is carried out using the data of the world DRAM market.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.682-691
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• 2005

We present a two-step evolution system that produces controllable virtual creatures in physically simulated 3D environment. Previous evolutionary methods for virtual creatures did not allow any user intervention during evolution process, because they generated a creature's shape, locomotion, and high-level behaviors such as target-following and obstacle avoidance simultaneously by one-time evolution process. In this work, we divide a single system into manageable two sub-systems, and this more likely allowsuser interaction. In the first stage, a body structure and low-level motor controllers of a creature for straight movement are generated by an evolutionary algorithm. Next, a high-level control to follow a given path is achieved by a neural network. The connection weights of the neural network are optimized by a genetic algorithm. The evolved controller could follow any given path fairly well. Moreover, users can choose or abort creatures according to their taste before the entire evolution process is finished. This paper also presents a new sinusoidal controller and a simplified hydrodynamics model for a capped-cylinder, which is the basic body primitive of a creature.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.57-68
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• 2011

This study approaches how newly emerged game companies has implemented strategies for product diversification according to market growth cycle(beginninggrowing-mature) by empirical case study through evolutionary theory and resource based theory approach. At the beginning, online game companies had grown with different strategies(technology based, service based) by initial condition(genre, technological level, user attribute). After market growth, for product diversification, these companies carried out path-dependent alliance strategy(complementary, competitive) depending on resource base(technology capacity, service capacity based). As online game market getting mature, these companies has adapted flexibly in responding to market growth cycle by integrated strategy(naturally selected to mobilize every possible resource capability). By analyzing the alliance strategies pattern of online game companies in newly emerged game industry according to market growth cycle through combination of resource based theory and evolutionary theory, these results suggest that new industrial, theoretical, policy model is required.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.554-566
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• 2014

An objective of VMS(Variable Message Signs) is to make transportation system effective specifically for driver's path selection. The traffic solutions including a VMS problem can be modeled through Game Theory, however, the majority of the studies can not model various driver's response according to VMS information in game theory. So, this paper tries to analyze a driver's response according to VMS traffic informations through evolutionary game theory. We apply a behavior characteristics of driver to evolutionary game theory, then finds drivers are only accepting in case of the biggest pay-off, and if a traffic flow finds a balance over time, ratio of accepting information is converged as an evolutionary stable state gradually. Consequently, the strategy of the other drivers such as traffic problems can not be predicted accurately. In case, drivers repeat between groups and reasonable judgment by the experience, we expect that VMS can provide strategic information through evolutionary game theory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2277-2298
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• 2019

Adaptive learning in e-learning has garnered researchers' interest. In it, learning resources could be recommended automatically to achieve a personalized learning experience. There are various ways to realize it. One of the realistic ways is adaptive learning path recommendation, in which learning resources are provided according to learners' requirements. This paper summarizes existing works and proposes an innovative approach. Firstly, a learner-centred concept map is created using graph theory based on the features of the learners and concepts. Then, the approach generates a linear concept sequence from the concept map using the proposed traversal algorithm. Finally, Learning Objects (LOs), which are the smallest concrete units that make up a learning path, are organized based on the concept sequences. In order to realize this step, we model it as a multi-objective combinatorial optimization problem, and an improved immune algorithm (IIA) is proposed to solve it. In the experimental stage, a series of simulated experiments are conducted on nine datasets with different levels of complexity. The results show that the proposed algorithm increases the computational efficiency and effectiveness. Moreover, an empirical study is carried out to validate the proposed approach from a pedagogical view. Compared with a self-selection based approach and the other evolutionary algorithm based approaches, the proposed approach produces better outcomes in terms of learners' homework, final exam grades and satisfaction.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.42.2-42.2
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• 2016

It is well known that theoretical models of Wolf-Rayet stars are not consistent with observational data in terms of temperature and stellar radius. Recent study in analytical and numerical simulations show the importance of density inhomogeneity in stellar envelope. Using 1-dimensional numerical simulations, we study how such clumpiness arisen over convective surface of Wolf-Rayet stars affect their evolutionary path. Starting from pure helium star models, we constructed 21 different initial conditions by varying stellar mass, metallicity, and the clumpiness of the sub-surface convection zone. We run the simulations until the oxygen-burning is reached and find that the influence of the clumpiness is sensitive to the initial metallicity. Our models with high metallicity including the effect of the density inhomogeneity can roughly explain the observed properties of Wolf-Rayet stars such as stellar radius and temperature. By contrast, despite a considerable amount of density inhomogeneity is given, low metallicity models could not fully explain observations. To understand the inconsistency in low metallicity models, detailed study with improved model is required, taking account of the error range of the observations.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.4
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• pp.567-584
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• 2013

This study aims to explore an evolutionary path of the IT service industry in Fairfax County using the Cluster Adaptive Cycle model in economic geography. The analysis is based on detailed historical and industrial information obtained through a variety of data sources including local archival materials, economic census, and interviews. This study also performs a shift-share analysis during the period of 1990 to 2011. Using the adaptive cycle model, the local IT service industry is indicated by a trajectory of constant cluster mutation. The evolution of the local IT service industry has been closely related to federal government policy due to the regional specificity of the National Capital Region and the proximity of the Department of Defense. Although the economic downturn of the late 2000s, the local IT service industry has been notable resilience and adapted to a changing market and technological environment. This constant mutation of the local industry is resulted from not only high resilience which is based on the large government procurement market, the reinforcement of adaptive capacity of the local firms and the network of economic agents such as firm and supporting institutions, but also high flexibility of the knowledge-based service industry to a changing business environment.