• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.271-276
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• 2001

Most engineers, related to soil and civil dynamic field, have been interested in the dynamic response of building transmitted from soil and rock to structure due to blasting. However it is not easy to estimate the dynamic response of structures and utilities due to blasting by using analytical method because of difficulties of soil modeling, prediction of excitation force and so on. In this paper, dynamic response analysis have been performed to predict vibration levels of structure due to blasting and the semi-empirical method. which is based on vibration measurement data. has been employed to consider blast vibration characteristics.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.336-339
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• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Especially, the performance of the prediction results in the high-level ozone concentration are not good. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering methods. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, the identification of nonlinear complex systems, and prediction of dynamical systems.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.10
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• pp.569-578
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• 2003

Data dependencies are one of major hurdles to limit ILP(Instruction Level Parallelism), so several related works have suggested that the limit imposed by data dependencies can be overcome to some extent with use of the data value prediction. Hybrid value predictor can obtain the high prediction accuracy using advantages of various predictors, but it has a defect that same instruction has overlapping entries in all predictor. In this paper, we propose a new hybrid value predictor which achieves high performance by using the information of static and dynamic classification. The proposed predictor can enhance the prediction accuracy and efficiently decrease the prediction table size of predictor, because it allocates each instruction into single best-suited predictor during the fetch stage by using the information of static classification. Also, it can enhance the prediction accuracy because it selects a best- suited prediction method for the “Unknown”pattern instructions by using the dynamic classification mechanism. Simulation results based on the SimpleScalar/PISA tool set and the SPECint95 benchmarks show the average correct prediction rate of 85.1% by using the static classification mechanism. Also, we achieve the average correction prediction rate of 87.6% by using static and dynamic classification mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2783-2804
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• 2021

In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2314-2333
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• 2023

It is significant to predict the performance degradation of complex electromechanical systems. Among the existing performance degradation prediction models, belief rule base (BRB) is a model that deal with quantitative data and qualitative information with uncertainty. However, when analyzing dynamic systems where observable indicators change frequently over time and working conditions, the traditional belief rule base (BRB) can not adapt to frequent changes in working conditions, such as the prediction of aeroengine performance degradation considering working condition. For the sake of settling this problem, this paper puts forward a new hidden belief rule base (HBRB) prediction method, in which the performance of aeroengines is regarded as hidden behavior, and operating conditions are used as observable indicators of the HBRB model to describe the hidden behavior to solve the problem of performance degradation prediction under different times and operating conditions. The performance degradation prediction case study of turbofan aeroengine simulation experiments proves the advantages of HBRB model, and the results testify the effectiveness and practicability of this method. Furthermore, it is compared with other advanced forecasting methods. The results testify this model can generate better predictions in aspects of accuracy and interpretability.

• Wind and Structures
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• v.24 no.4
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• pp.351-365
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• 2017

The minimization method is widely used to predict the dynamic characteristics of a system. Generally, data recorded by experiment (for example displacement) tends to contain noise, and the error in the properties of the system is proportional to the noise level (NL). In addition, the accuracy of the results depends on various factors such as the signal character, filtering method or cut off frequency. In particular, coupled terms in multimode systems show larger differences compared to the true value when measured in an environment with a high NL. The iterative least square (ILS) method was proposed to reduce these errors that occur under a high NL, and has been verified in previous research. However, the ILS method might be sensitive to the signal processing, including the determination of cutoff frequency. This paper focused on improving the accuracy of the ILS method, and proposed the modified ILS (MILS) method, which differs from the ILS method by the addition of a new calculation process based on correlation coefficients for each degree of freedom. Comparing the results of these systems with those of a numerical simulation revealed that both ILS and the proposed MILS method provided good prediction of the dynamic properties of the system under investigation (in this case, the damping ratio and damped frequency). Moreover, the proposed MILS method provided even better prediction results for the coupling terms of stiffness and damping coefficient matrix.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.163-173
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• 2018

This paper performed the prediction of the acoustic loads applied to the surface of the flight vehicle during flight. Acoustic loads during flight arise from the pressure fluctuations on the surface of body. The conventional method of predicting the acoustic loads in flight uses semi-empirical method derived from theoretical and experimental results. However, there is a limit in obtaining the flow characteristics and the boundary layer parameters of the flight vehicle which are used as the input values of the empirical equation through experiments. Therefore, in this paper, we use the hybrid method which combines the results of CFD (Computational Fluid Dynamics) with semi-empirical methods to predict the acoustic loads acting on flight vehicle during flight. For the flight vehicle with cone-cylinder-flare shape, acoustic loads were estimated for the subsonic, transonic, supersonic, and Max-q (Maximum dynamic pressure) condition flight. For the hybrid method, two kind of boundary layer edge estimation methods based on CFD results are compared and the acoustic loads prediction results were compared according to empirical equations presented by various researchers.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.353-361
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• 2020

VVC (Versatile Video Coding) is a new video compression technique that is being standardized, and it supports HD / UHD / 8K video, and High Dynamic Range (HDR) video with a goal of approximately 2 times higher coding efficiency than the conventional HEVC. It also aims to support a variety of functionalities such as screen content coding, adaptive resolution changes, and independent sub-pictures. In this paper, we investigate the signaling process of intra prediction mode first, and develop an effective coding method of the chroma intra prediction mode. In case of the DM mode, the proposed method simplifies the prediction mode of the chorma intra prediction mode when referring to the angular mode of the luminance block. It can improve coding efficiency of the chroma intra prediction mode, and the proposed process can also consider the size of the block in order to further improve its coding efficiency.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.79-84
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the autoregressive and moving average model with auxiliary stochastic input (ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then, the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story building model subject to ground exitations.

• International Journal of Fluid Machinery and Systems
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• v.8 no.2
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• pp.63-72
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• 2015

Water hammer phenomena are important issues for the design and the operation of hydro power plants. Especially, if several reversible pump-turbines are coupled hydraulically there may be strong unit interactions. The precise prediction of all relevant transients is challenging. Regarding a recent pump-storage project, dynamic measurements motivate an improved turbine modeling approach making use of a Thoma number dependency. The proposed method is validated for several transient scenarios and turns out to improve correlation between measurement and simulation results significantly. Starting from simple scenarios, this allows better prediction of more complex transients. By applying a fully automated simulation procedure broad operating ranges of the highly nonlinear system can be covered providing a consistent insight into the plant dynamics. This finally allows the optimization of the closing strategy and hence the overall power plant performance.