• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1171-1173
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• 1997

This paper presents the sliding mode observer-model following(SMO-MF) power system stabilizer(PSS) for unmeasurable plant state variables. This SMO-MF PSS can be obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the linear foil-order observer(LFOO).

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.213-219
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• 2000

Combination of AHP priorities is essential in combining opinions of multiple experts. There are two ways to get combined priorities: one is to combine the pairwise matrices and obtain the priority from it and another is to combine the individual priorities. In this paper, we use a Dirichlet probability model to combine the priorities from multiple experts. The resulting combined priority is an expected value of the model, which is a function of some measure of the homogeneity and credibility of the group of experts. We give some interpretations of this measure and illustrate them by numerical example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.899-902
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• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.609-616
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• 2003

The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference Adaptive Speed Control system of a diesel engine, in which PID control system for the model of a diesel engine is adopted as the nominal model and Fuzzy controller and derivative operator are adopted as the adaptive controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.102-108
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• 2006

In this paper, we propose an interference cancellation(IC) scheme using a partial Rake(PRAKE) combining in ultra-wideband(UWB) multipath fading channels. In this IC scheme, differently from the conventional transmitter model, which employs a guard interval between each frame, the guard interval is employed between each slot for estimating the multiple access interference(MAI). The UWB systems using the proposed IC scheme have little performance degradation without regard to the number of user, while the conventional UWB systems have a significant performance degradation according to the number of user. In order to reduce the receiver complexity, the PRAKE combining of post-canceled signal and the partial user IC scheme are also proposed.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.35-40
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• 2011

In this paper, we analyze that co-channel interference mitigation algorithms MMSE (Minimum Mean Square Error), OC (Optimal Combining), ML (Maximum Likelihood) using 2.4Ghz in WBAN (Wireless Body Area Network) system. Also analyze that scenario and channel model by IEEE 802.15.6. ML gives the best performance for all simulation. ML and OC have high complexity than MMSE complexity, because these algorithms should be known channel information of interference users. So these algorithms are difficult to apply to WBAN. Therefore we will study the interference mitigation algorithm that should be accomplished trade-off of between efficiency and complexity.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.12
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• pp.1218-1226
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• 2004

This paper presents thermal behaviors and performances of a fresh air load reduction system by using earth tube system combined with air-heated solar collector. The earth tube system reduces a fresh air load by heat exchange with soil throughout the year. In the previous experimental research, it was clarified that the earth tube system was very useful as a fresh air load reduction system. However, since outlet temperature of the fresh air which was heated by earth tube system was below 15$^{\circ}C$ in winter, it is not suitable to introduce the fresh air into the place of residence directly. Therefore, a simulation model using the simple heat diffusion equation was used to examine a rising effect of outlet air temperature in winter by combining with air-heated solar collector. An improvement of annual performance by control of operation is also quantitatively examined. In conclusion, it is confirmed that its performance is improved by control of operation throughout the year and outlet air temperature rose by combining with air-heated solar collector.