• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.127-142
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• 2023

The management of size and weight, which are the growth information of aquaculture fish in fish-farms, is the most basic goal. In this study, the epoch is defined in fish-farms from the time of stocking or dividing to the time of shipment, and the growth data for a total of three epoch is analyzed from a time series perspective. Growth information such as the size and weight of aquaculture fish that occur over time in fish-farms is compared and analyzed with water quality environmental information and feeding information, and a model is presented using the analysis results. In this study, linear, exponential, and logarithmic regression models are presented using the Box-Jenkins method for size and weight by epoch using data obtained in the field.

• Smart Media Journal
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• v.13 no.6
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• pp.24-34
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• 2024

If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.1-9
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• 2024

In this paper, we propose a comparative analysis to evaluate the impact of activation functions and attention mechanisms on the performance of time-series models for Mars meteorological data. Mars meteorological data are nonlinear and irregular due to low atmospheric density, rapid temperature variations, and complex terrain. We use long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU) architectures to evaluate the effectiveness of different activation functions and attention mechanisms. The activation functions tested include rectified linear unit (ReLU), leaky ReLU, exponential linear unit (ELU), Gaussian error linear unit (GELU), Swish, and scaled ELU (SELU), and model performance was measured using mean absolute error (MAE) and root mean square error (RMSE) metrics. Our results show that the integration of attentional mechanisms improves both MAE and RMSE, with Swish and ReLU achieving the best performance for minimum temperature prediction. Conversely, GELU and ELU were less effective for pressure prediction. These results highlight the critical role of selecting appropriate activation functions and attention mechanisms in improving model accuracy for complex time-series forecasting.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.41-47
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• 2010

In this paper, we show the performance evaluation of outlier detection methods based on the GARCH model. We first introduce GARCH model and the methods of outlier detection in the GARCH model. The results of small simulation and the real KOSPI data show the out-performance of the outlier detection method over the traditional method in the GARCH model.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1715-1721
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• 2011

For an efficient railroad operations the demand forecasting is required. Time series models can quickly forecast the future demand with fewer data. As well as the accuracy of forecasting is excellent compared to other methods. In this study is proposed the intervention ARIMA model for forecasting methods of KTX passenger demand. The intervention ARIMA model may reflect the intervention such as the Kyongbu high-speed rail project second phase. The simple seasonal ARIMA model is predicted to overestimate the KTX passenger demand. However, intervention ARIMA model is predicted the reasonable results. The KTX passenger demands were predicted to be a week units separated by the weekday and weekend.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.543-549
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• 2005

This paper deals with modeling and analysis fer the landing motion of a human-body model. First, the dynamic model of a floating human body is derived. The external impulse exerted on the ground as well as the internal impulse experienced at the joints of the human body model is analyzed. Second, a motion planning algorithm exploiting the kinematic redundancy is suggested to ensure stability in terms of ZMP stability condition during a series of landing phases. Four phases of landing motion are investigated. In simulation, the external and internal impulses experienced at the human joints and the ZMP history resulting from the motion planning are analyzed for two different configurations. h desired landing posture is suggested by comparison of the simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.401-406
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• 2004

In this paper, a new time-domain adaptive predistortion scheme is proposed to compensate for the nonlinearity of high power amplifiers (HPA) in OFDM systems. A complex Wiener-Hammerstein model (WHM) is adopted to describe the input-output relationship of unknown HPA with linear dynamics, and a power series model with memory (PSMWM) is used to approximate the HPA expressed by WHM. By using the PSMWM, the compensation input to HPA is calculated in a real-time manner so that the linearization from the predistorter input to the HPA output can be attained even if the nonlinear input-output relation of HPA is uncertain and changeable. In numerical example, the effectiveness of the proposed method is confirmed and compared with the identification method based on PSMWM.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.73-82
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• 2000

This study was implemented to find an optimal model for wastewater treatment processes using PHOENICS(Parabolic, hyperbolic or Elliptic Numerical Integration Code Series) and ASM(Activated Sludge Model). PHOENICS is a general software based upon the laws of physics and chemistry which govern the motion of fluids, the stresses and strains in solids, heat flow, diffusion, and chemical reaction. The wastewater flow and removal efficiency of particle in two phase system of a grit chamber in wastewater treatment plant were analyzed to inquire the predictive aspect of the operational model. ASM was developed for a biokinetic model based upon material balance in complex activated sludge systems, which can demonstrate dynamic and spatial behavior of biological treatment system. This model was applied to aeration tank and settling chamber in Choonchun city, and the modeling result shows dynamic transport in aeration tank. PHOENCS and ASM could be contributed for the optimal operation of wastewater treatment plant.

• Water for future
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• v.20 no.2
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• pp.107-116
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• 1987

The stochastic model has been developed for synthetic generation of hydrologic series that would be needed in the analysis, planning, design and operation of water resources system. In this study, after generating the yearly streamflows by multisite AR(1) model using the historical data in the Han River Basin, the monthly streamflows is generated by the disaggregation model. The model is verified of its applicability to domestic rivers, which is obtained through the statistical analysis and good ness of fit test using synthetic streamflows generated.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.79-86
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• 2000

This paper presents the results of a parametric study on the behavior of tunnel face reinforced with horizontal pipes. A series of reduced-scale model tests was carried out to in an attempt to verify previously performed three-dimensional numerical modeling and to investigate effects of reinforcement layout on the tunnel face deformation behavior The results of model tests indicate that the tunnel face deformation can significantly reduced by pre-reinforcing the tunnel face with longitudinal members and thus enhancing the tunnel stability. In addition, the model tests results compare fairly well with those from the previously performed three-dimensional finite element analysis. Therefore, a properly calibrated three dimensional model may effectively be used in the study of tunnel face reinforcing technique.