• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.153-166
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• 2003

This study presents the time-divided forecasting model to integrate evolutionary optimization algorithm and change point detection based on artificial neural networks (ANN) for the prediction of (Korea) stock price index. The genetic algorithm(GA) is introduced as an evolutionary optimization method in this study. The basic concept of the proposed model is to obtain intervals divided by change points, to identify them as optimal or near-optimal change point groups, and to use them in the forecasting of the stock price index. The proposed model consists of three phases. The first phase detects successive change points. The second phase detects the change-point groups with the GA. Finally, the third phase forecasts the output with ANN using the GA. This study examines the predictability of the proposed model for the prediction of stock price index.

• Korean Journal of Logic
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• v.12 no.2
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• pp.171-199
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• 2009

This essay will consider evolutionary views that attempt to capture the continuity of theory-change from Newtonian to Einsteinian physics via the formal aspects of these theories. Although it cannot be denied that the formal aspects such as 'correspondence principles' and 'covariance principles' provide important information concerning this theory-change, these formal properties are not sufficient to capture the essential elements of any evolutionary account of the development of Einstein's special and general theories of relativity from Newtonian mechanics.

• Journal of Global Scholars of Marketing Science
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• v.7
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• pp.71-103
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• 2001

Marketing practice varies among firms. However, the prescriptive literature emphasises a universal view of practice, a 'one size fits all' view. This paper addresses the issue of explaining diversity in marketing practice in competitive space and in time. Diversity in competitive space reflects the existence of different routes to high performance. Diversity in time reflects some combination of change in the individual firm and change in a population of firms. In the former case, diversity is shaped by organisational change; in the latter by the disbandment and founding of firms in the population. In so far as diversity is the norm, the manner in which practice will be shaped by evolutionary processes is considered. Fnally, the role of the academy as one of the forces driving the evolutionary process is discussed. Miles and Snow's (1978, 1986) work is taken as a main point of departure in the search for explanation and ecological and evolutionary concepts are drawn on for support and to suggest an explanation for the nature of diversity over time.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.44-57
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• 2015

In recent years, for the purpose of solving the problem regarding environment protection and resource saving, certain measures and policies have been promoted to establish a reverse supply chains (RSCs) with material flows from collection of used products to reuse the recycled parts in production of products. It is necessary to analyze behaviors of RSC members to determine the optimal operation. This paper discusses a RSC with a retailer and a manufacturer and verifies the behavior strategies of RSC members which may change over time in response to changes parameters related to the recycling promotion activity in RSC. A retailer takes two behaviors: cooperation/non-cooperation in recycling promotion activity. A manufacturer takes two behaviors: monitoring/non-monitoring of behaviors of the retailer. Evolutionary game theory combining the evolutionary theory of Darwin with game theory is adopted to clarify analytically evolutionary outcomes driven by a change in each behavior of RSC members over time. The evolutionary stable strategies (ESSs) for RSC members' behaviors are derived by using the replicator dynamics. The analysis numerically demonstrates how parameters of the recycling promotion activity: (i) sale promotion cost, (ii) monitoring cost, (iii) compensation and (iv) penalty cost affect the judgment of ESSs of behaviors of RSC members.

• Journal of Korean Elementary Science Education
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• v.37 no.3
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• pp.233-253
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• 2018

Since open inquiry of science was formally introduced at the 2007 Revised Science Curriculum Course, the purpose and effect of it has been positively evaluated, and it is underlined continuously until the revised science education course in 2015. However, through many previous studies, there is still a lack of awareness of open inquiry of both students and teachers in the field, and it was revealed they are continually appealing confusion and difficulties. Therefore, in this research, we analyzed the causes that make it difficult to execute open inquiry, and developed differentiated open inquiry guide materials that can contribute to the realization of teachers and students. They were developed by the brain-based evolutionary approach to provide students with authentic science. The brain-based evolutionary approach is reflecting the evolutionary attributes and the brain functions associated activities of scientists. It was revealed that, in the same way as the pilot test results, the usefulness of the differentiated guide materials were very high, and there was a statistically significant difference in the science attitude. It was found that the application of the brain-based evolutionary approach had positively influenced the stage of determining the inquiry themes, and self-confidence that could be able to do as a scientist. Analysis of top and sub group types on the basis of inquiry ability showed that both groups are improved at science attitude by the differentiated guide materials. There was a positive effect on change in the self-perception of scientific creativity. We were able to see a positive change in the post survey for open inquiry-efficacy. The developed differentiated open inquiry guide materials contributed to the improvement of open inquiry-efficacy for both the teacher and student.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.503-506
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• 2005

In this study, optimization design technique for control of solid-fluid coupled force (sloshing) using evolutionary method is suggested. Artificial neural networks(ANN) and genetic algorithm(GA) is employed as evolutionary optimization method. The ANN is used to analysis of the sloshing and the genetic algorithm is adopted as an optimization algorithm. In the creation of ANN learning data, the design of experiments is adopted to higher performance of the ANN learning using minimum learning data and ALE(Arbitrary Lagrangian Eulerian) numerical method is used to obtain the sloshing analysis results. The proposed optimization technique is applied to the minimization of sloshing of the water in the tank lorry with baffles under 2 second lane change.

• Biomolecules & Therapeutics
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• v.25 no.1
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• pp.57-68
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• 2017

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.180-187
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• 2001

This paper proposes an efficient evolutionary programming algorithm for solving a generation expansion planning(GEP) problem known as a highly-nonlinear dynamic problem. Evolutionary programming(EP) is an optimization algorithm based on the simulated evolution (mutation, competition and selection). In this paper, new algorithm is presented to enhance the efficiency of the EP algorithm for solving the GEP problem. By a domain mapping procedure, yearly cumulative capacity vectors are transformed into one dummy vector, whose change can yield a kind of trend in the cost value. To validate the proposed approach, this algorithm is tested on two cases of expansion planning problems. Simulation results show that the proposed algorithm can provide successful results within a resonable computational time compared with conventional EP and dynamic programming.

• Journal of TMJ Balancing Medicine
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• v.8 no.1
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• pp.6-10
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• 2018

In order to propose a fundamental and appliable theories for balancing therapy of temporomandibular joint (TMBT), evolutionary proofs and up-down theories in evolutionary biology and Korean medicine were investigated. Balancing therapy of temporomandibular joint treats disorder and diseases of the whole body through straightening of the abnormal linking between temporomandibular joint and axis. Although the mechanism of this therapy contains many merits like multicellular integrity and coadjustment, ease of balance and alert forward mobility by the bipedal stepping and evolution to Homo sapiens, increasing disadvantages of balancing pressure of right and left in the lengthened perpendicular axis and the balancing load of temporomandibular joint and axis following the reactional change of dental occlusion are deeply related and considered in this therapy. As for up-down theory, crossing of heavenly qi and earth qi centering on cervical joint is presented as the first mechanism for TMBT, and the other ones like in-out and up-down qi activity of tripple energizer, up-down of essence-qi-spirit in the three backbone barrier and three cinnabar field, up-down of yin-yang-water-fire of viscera and bowels can be related too.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.158-163
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• 1998

This paper is our first attempt to construct a information processing system such as the living creatures' brain based on artificial life technique. In this paper, we propose a method of constructing neural networks using bio-inspired emergent and evolutionary concept, Ontogeny of living things is realized by cellular automata model and Phylogeny that is living things adaptation ability themselves to given environment, are realized by evolutionary algorithms. Proposing evolving cellular automata neural systems are calledin a word ECANS. A basic component of ECANS is 'cell' which is modeled on chaotic neuron with complex characteristics, In our system, the states of cell are classified into eight by method of connection neighborhood cells. When a problem is given, ECANS adapt itself to the problem by evolutionary method. For fixed cells transition rule, the structure of neural network is adapted by change of initial cell' arrangement. This initial cell is to become a network b developmental process. The effectiveness and the capability of proposed scheme are verified by applying it to pattern classification and robot control problem.