• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2000년도 춘계학술발표대회
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• pp.133-136
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• 2000

In recent years, hybrid neural network approaches which combine neural networks and mechanistic models have been gaining considerable interests. These approaches are potentially very efficient to obtain more accurate predictions of process dynamics by combining mechanistic and neural models in such a way that the neural network model properly captures unknown and nonlinear parts of the mechanistic model. In this work, such an approach was applied in the modeling of a full-scale coke wastewater treatment process. First, a simplified mechanistic model was developed based on the Activated Sludge Model No.1 and the specific process knowledge, Then neural network was incorporated with the mechanistic model to compensate the errors between the mechanistic model and the process data. Simulation and actual process data showed that the hybrid modeling approach could predict accurate process dynamics of industrial wastewater treatment plant. The promising results indicated that the hybrid modeling approach could be a useful tool for accurate and cost-effective modeling of biochemical processes.

• 대한인간공학회지
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• 제20권2호
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• pp.29-46
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• 2001

This study is about the modeling of comfort feeling structure in indoor environments. To represent the degree of practical comfort feeling level in an environment, we measured elements of human sense and resultant elements of comfort feeling such as coziness, refreshment, and freshness with physical values(temperature, illumination, noise. etc.). The relationships of elements of human sense and elements of comfort feeling were formulated as a fuzzy model. And a hybrid-neural network with three layers were designed where obtained from fuzzy membership function values of the elements of human sense were used as inputs, and given as fuzzy membership function values of resultant elements of comfort feeling were used as outputs. Both kinds of fuzzy membership function values were obtained from physical values. The network was trained by measured data set. The proposed hybrid-neural network were tested and proposed a more realistic model of comfort feeling structure in indoor environments.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1245-1247
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• 2004

This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.

• 방송공학회논문지
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• 제16권2호
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• pp.360-371
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• 2011

T-DMB 하이브리드 데이터 서비스는 서비스를 구성하는 장면 기술 정보와 객체 기술 정보를 방송망 이외의 전송 경로를 통해 분산 전송할 수 있도록 구성하는 하이브리드 BIFS 기술을 이용하여 기존 T-DMB 수신기와의 역호환성을 보장하면서 새로운 데이터 서비스를 제공한다. 본 논문에서는 하이브리드 BIFS 기술을 이용하여 분산 전송이 가능한 BIFS를 구성하기 위한 하이브리드 서비스 저작 프레임워크의 구현 결과와 이를 이용한 실험 결과를 소개한다. 하이브리드 서비스 저작 프레임워크는 서비스 생성 시스템, 서비스 관리 시스템, 콘텐츠 제공 시스템 등으로 구성되며, 통합된 하이브리드 서비스를 저작하는 것은 물론 이를 방송망으로 전송되는 데이터와 무선 통신망을 통해 전송되는 개인맞춤형 데이터로 분할하여 생성하고 관리하는 기능을 제공한다. 이 서비스 프레임워크를 통해 구현된 콘텐츠는 기존 수신기와의 역호환성을 보장하면서 새로운 개인맞춤형 데이터 서비스 구현이 가능함을 검증하였다.

• IEIE Transactions on Smart Processing and Computing
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• 제3권5호
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• pp.325-330
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• 2014

The era of convergence is being applied to all areas of Information and Communication Technology (ICT). The convergence of broadcasting service and communication service almost occurs on smart devices including smartphone. The smart hybrid Digital Multimedia Broadcasting (DMB) is a typical example of the convergence of broadcasting and wireless communication service. The hybrid mobile broadcasting service can support seamless video, 3D, high quality, and additional data services based on network connection between the broadcasting and wireless network. The gateway and terminal (including apps on the smartphone) take the role of the main components on the hybrid service. This paper presents the service concept, main components structure, the implementation of gateway and terminals, and field test to the urban areas for the mobile hybrid system.

• 한국통신학회논문지
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• 제30권7B호
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• pp.427-432
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• 2005

광대역 멀티미디어의 고품질 서비스를 제공하기 위한 가입자 전송 망 분야의 변화가 요구 되고 있는 요즘, PON에 대한 연구가 이를 실현시키기 위한 방안으로 크게 부각되고 있다. 본 논문에서는 SUCCESS(Stanford University aCCESS : next generation hybrid WDM/TDM optical access network architecture) 구조에서의 WDM-PON을 위한 스케줄링 알고리즘을 제안하고자 한다. 경제적 구현을 실현하기 위해서는 공유되는 자원의 보다 효율적인 할당이 필요하며, 이를 위해 SUCCESS의 구조와 특성에 적절한 효율적인 스케줄링 알고리즘을 제안하고 있으며, 전체 시스템에서의 평균 패킷 지연시간 및 처리량에 대한 성능을 평가, 분석한다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• 한국통신학회논문지
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• 제30권10B호
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• pp.630-638
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• 2005

네트워크 및 종단 노드의 시스템에 걸친 제한된 자원을 활용하여 실현되는 영상/음성 전달 서비스를 위한 멀티미디어 응용 프로그램의 품질을 보장하기 위해서는 지연, 지터, 손실과 같은 전송 상태와 CPU, 메모리의 사용량과 같은 시스템의 상태를 동시에 관찰하는 것이 필요하다. 본 논문에서는 액세스그리드 (Access Grid) 경우와 같이 IP 멀티캐스트 상에 동작하는 RTP/RTCP에 기반한 실시간 미디어 응용 프로그램을 대상으로 동적/정적 모니터링 방식을 혼용하여 멀티캐스트 상태와 시스템 상태를 측정하는 혼성 모니터링 방식을 제안한다. 또한 종단간 전송 품질이 저하된 경우 제안한 모니터링 방식에서 측정된 결과를 비교/분석하여 품질 저하의 원인을 판단하고 원인에 적합한 대응방안을 연계하고i라 한다. 이 결과를 바탕으로 네트워크/시스템의 상태 변화에 적응적인 영상/음성 전송 서비스의 가능성을 타진하고 종단간 전송 품질 저하 방지를 위한 효과를 예상한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.994-998
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• 1996

We propose an approach to integrating fuzzy logic control with RBF(Radial Basis Function) networks and show how the integrated network can be applied to multivariable self-organizing and self-learning fuzzy controller. Using the hybrid learning algorithm. To investigate its usefulness and performance, this controller is applied to a time-delayed process system. Simulation results show good control performance and fast convergency in hybrid loaming method.