• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.579-584
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• 2003

All of propagation path loss prediction models, which have been presented up to date, are oかy for ground living space. In reality, sea surface free space is different from ground living space in physical hierarchical structure. If the propagation path prediction model for ground living space is applied to the sea surface free space, propagation path loss will be smaller than actual value, while the maximum service straight line will become shorter. Thus this paper proposed and simulated the propagation path loss prediction model for predicting propagation path loss more accurately in sea surface free space, with its focus on CDMA mobile communication frequency band. Then the simulation results were compared to actual survey to verify its practicality.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.324-330
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• 2005

For axial-type turbines which operate at partial admission, a performance prediction model is developed. In this study, losses generated within the turbine are classified to windage loss, expansion loss and mixing loss. The developed loss model is compared with experimental results. Particularly, if a turbine operates at a very low partial admission rate, a circular-type nozzle is more efficient than a rectangular-type nozzle. For this case, a performance prediction model is developed and an experiment is conducted with the circular-type nozzle. The predicted result is compared with the measured performance, and the developed model quite well agrees with the experimental results. So the developed model could be applied to predict the performance of axial-type turbines which operate at various partial admission rates or with different nozzle shape.

• The KSFM Journal of Fluid Machinery
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• v.9 no.4 s.37
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• pp.13-19
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• 2006

For axial-type turbines which operate at partial admission, a performance prediction model is developed. In this study, losses generated within the turbine are classified to windage loss, expansion loss and mixing loss. The developed loss model is compared with experimental results. Particularly, if a turbine operates at a very low partial admission rate, a circular-type nozzle is more efficient than a rectangular-type nozzle. For this case, a performance prediction model is developed and an experiment is conducted with the circular-type nozzle. The predicted result is compared with the measured performance, and the developed model quite well agrees with the experimental results. So the developed model could be applied to predict the performance of axial-type turbines which operate at various partial admission rates or with different nozzle shape.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.574-579
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• 2000

In this study. an off-design performance prediction program for centrifugal pumps is developed. To estimate the losses in an impeller flow passage, two-zone model and two-element in series(TEIS) model are used. At impeller exit. the mixing process occurs with an increase in entropy. In two-zone model. there are both primary zone and secondary zone for an isentropic core flow and an average of all non-isentropic streamtubes respectively. The level of the core flow diffusion in an impeller was calculated by using TEIS model. While internal losses in an impeller an automatically estimated by using the above models, some empirical correlations far estimating external losses. far example, disk friction loss, recirculation loss and leakage loss are used. In order to analyze the vaneless diffuser flow. the momentum equations for the radial and tangential directions are used and solved together with continuity and energy equations.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2676-2681
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• 2008

In previous studies, Convex cyclone are proposed to reduce pressure loss which are design cyclone wall with a single continuous curve. Studies about a prediction model for pressure loss and cut-size has focused on conventional cylinder-on-con cyclone. Therefore, the models do not perform well for uncommon design. In this study, a predict model for pressure loss and cut-size depend on cyclone wall curvature are developed. The tangential velocity below vortex-finder is obtained with consideration about friction area and momentum loss on the cyclone wall, and with this the variation of vortex-core and core velocity is obtained. Pressure loss is predicted using a Rankine vortex hypothesis. The prediction results are well agreed with experiments and CFD results.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.2
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• pp.165-170
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• 2013

This paper presents the iron loss prediction of rotating electric machines taking account of the vector hysteretic properties of electrical steel sheet. The E&S vector hysteresis model is adopted to describe the vector hysteretic properties of a non-oriented electrical steel sheet, and incorporated into finite element analysis (FEA) for magnetic field analysis and iron loss prediction. A permanent magnet synchronous generator is taken as a numerical model, and the analyzed magnetic field distribution and predicted iron loss by using the proposed method is compared with those from a conventional method which employs an empirical iron loss formula with FEA based on a non-linear B-H curve. Through the comparison the effectiveness of the presented method for the iron loss prediction of the rotating machine is verified.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.1
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• pp.70-78
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• 1998

The present study has tested semi-empirical loss models for a reliable performance prediction of mixed-flow pumps with four different specific speeds. In order to improve the predictive capabilities, this paper recommends a new internal loss model and a modified parasitic loss model. The prediction method presented here is also compared with that based on two-dimensional cascade theory. Predicted performance curves by the proposed set of loss models agree fairly well with experimental data for a variety of mixed-flow pumps in the normal operating range, but further studies considering 'droop-like' head performance characteristic due to flow reversal in mixed-flow impellers at low flow range near shut-off head are needed.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.61-68
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• 2020

E-sports has grown steadily in recent years and has become a popular sport in the world. In this paper, we propose a win-loss prediction model of League of Legends at the start of the game. In League of Legends, the combination of a champion statistics of the team that is made through each player's selection affects the win-loss of the game. The proposed model is a deep learning model based on Bidirectional LSTM embedding which considers a combination of champion statistics for each team without any domain knowledge. Compared with other prediction models, the highest prediction accuracy of 58.07% was evaluated in the proposed model considering a combination of champion statistics for each team.

• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.3
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• pp.10-17
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• 2005

A performance prediction model is developed for partially admitted axial-type turbines. Losses generated within the turbine are classified to the windage loss, expansion loss and mixing loss. The developed loss model is compared with an experimental result. The results predicted with the developed model agree well with the experimental results than those predicted with several other models because this model considers three different kinds of losses. Moreover, this model predicts well the performance even the partial admission is changed. So, this model could be applied to predict the performance of partially admitted axial turbine and it has a high accurate performance.