• 한국지능시스템학회논문지
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• 제16권5호
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• pp.635-641
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• 2006

Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and infer the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

• 산업경영시스템학회지
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• 제47권2호
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• pp.116-123
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• 2024

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

• 한국동물학회:학술대회논문집
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• 한국동물학회 1994년도 한국생물과학협회 학술발표대회
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• pp.228.1-228
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• 1994

No Abstract, See Full Text

• 농촌계획
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• 제14권2호
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• pp.99-110
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• 2008

The purposes of this paper are first, to develop and adapt auditing methodology of rural amenity resource investigation and second, to propose strategic planning of amenity web data base system. Relating with auditing methodology, we make the life cycle of rural amenity resource investigation based on value chain method. we make 8 stage of auditing process and 105 auditing items in details. We adapt these guidelines in real world and then improve developed methodology. Therefore we expect to promote the quality and accuracy of investigation project using these guidelines. Relating with blue print of strategic planning, we first analyse external environment about Competitors, Suppliers, New entrants, Buyers, Substitutes with 5 force model for amenity information system. We second make the blue print of strategic planning of amenity web data base system project. Then we propose the FIRST, BEST, MOST strategy of amenity web data base system and the web hub system.

• 경영과학
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• 제28권3호
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• pp.125-141
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• 2011

We have recently witnessed many of global companies did not successfully adapt themselves to local markets, and finally exited the markets experiencing failures. The purpose of this study is to suggest practical glocalization strategies for global e-service companies to run their respective businesses in local markets with success. Glocalization is a terminology blending globalization and localization, meaning that global companies adapt themselves to local cultures, environment, languages, laws and regulations so as to survive and prosper in those markets while maintaining high quality of standards and processes they originally have for global competitive edge. Examining success stories as well as failure ones of global e-service companies having entered Asian markets, we provide marketing mix strategy for successful glocalization, and suggest some guidelines for prospective e-service companies wishing to enter local markets with different cultures and languages to fit themselves to new environments.

• 통상정보연구
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• 제11권3호
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• pp.25-45
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• 2009

The e-Trade environment has enabled the complex trade processes to be automated using e-Trade information systems, which had been manually processed through many trade-related parties in the past. Korea has completed the development of the most advanced e-Trade platform called "u-Trade Hub," which can process automatically all the trade-related activities from marketing to payment. It is anticipated for the world trade environment to have more FTAs throughout the world and this will complicate the trade processes more and more in the future. This means the constant cost-bearing updates of the e-Trade environment to adapt the process changes brought by new FTAs with other countries. In this paper, we propose the systematic approach to easily as well as less costly adapt the possible trade process changes resulted from the future FTAs by adopting a rule base management system. The prototype system to test the applicability of the proposed approach is developed using Win-Prolog 4.8 environment.

• 디지털융복합연구
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• 제10권10호
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• pp.277-282
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• 2012

음성 인식 시스템은 다양하게 변화하는 환경 잡음에 빠르게 적응할 수 없어서 인식 성능을 저하시키는 요인이 된다. 본 논문에서는 평균 예측 LMS 알고리즘을 이용하여 반향 잡음에 강인하게 하는 방법으로 HMM 학습 모델을 구성하는 방법을 제안하였으며, 변화하는 반향 잡음에 적응하도록 HMM 학습 모델을 구성하여 인식 성능을 평가하였다. 실험 결과 변화하는 환경 잡음을 제거하여 얻은 음성의 SNR은 평균 3.1dB이 향상되었고 인식률은 3.9% 향상되었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.97-100
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• 2001

A common network such as internet does not provide a guaranteed network bandwidth to accommodate multimedia service in a reliable fashion. In this paper, we propose a new rate control mechanism for multimedia service on the internet which is adaptive to the dynamic QoS in real-time. Also we adapt an QoS monitoring module and real-time transmission control module to adapt dynamic network bandwidth. To do this, we used layer attribution of media data and also considered loss rate and buffer threshold in receiver side for measurement of dynamic QoS.

• 한국정보전자통신기술학회논문지
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• 제5권2호
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• pp.81-88
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• 2012

Future vehicle must be both driver-friendly and able to adapt to changes in the road's conditions. The system is needed to adapt to both the driver and the circumstance for maximum convenience and safety. In order to solve these problems, this paper proposes an algorithm for developing smart vehicles. In this paper, it is simulated to compare the performance of a normal car with that of the algorithm-implemented vehicle in a potential accident. Through the computer simulation, it proved that the algorithm-implemented vehicle automatically adjusted the mirrors and seat for the maximum comfort and driver's awareness of the circumstance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1020-1024
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• 2005

In this paper, an approach to dynamic systems control is addressed based on exploiting the potential features of the new nonlinear neural oscillator. Neural oscillators have recently enabled robots to exhibit natural dynamics using their robustness and entrainment properties. To technically accomplish this objective, the neural oscillator should be connected to the robot joints under the sensory feedback. This also requires the neural oscillator to adapt to the non-periodic nature of arbitrary input patterns. However, even in the most widely-used Matsuoka oscillator, when an unknown quasi-periodic or non-periodic signal is applied, its output signal is not always closely entrained. Therefore, current neural oscillators may not be applied to the precise control of the dynamic systems response. We illustrate the enhanced entrainment properties of the new neural oscillator by numerical simulation and show the possibility for implementation to control a variety of dynamic systems. It is verified that the oscillator can produce rhythmic signals for generating actuator signals which can be naturally modified by incorporating sensory feedback to adapt to outer circumstances.