• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.217-219
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• 2006

4G mobile networks are expected to support various multimedia services over IP networks and also satisfy high spectral efficiency requirement. In cellular systems including 4G networks, hotspot cells can occur when available wireless resources at some location are not enough to sustain the needs of users. The hotspot cell can potentially lead to blocked and dropped calls, which can deteriorate the service quality for users. In a 4G mobile network, a band of users enjoying multimedia services can move around, which may generate heavy flows of traffic load. This situation can generate the hotspot cell which has a short life span of only a few minutes. In this paper, we propose a handover-based scheme which can effectively manage hotspot cells in 4G mobile networks. With the scheme, the current serving cell can recognize the load status of the target cell in advance before handover execution. Adaptive handover time control according to the amount of traffic load of cells can effectively and flexibly manage the hotspot cell in the network. And, through our hotspot cell management scheme, acceptable service quality can be supported as users continuously maintain connections with the network. In the simulation results, we find that our scheme generates smaller number of hotspot cells and supports higher service quality than the compared schemes.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.131-140
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• 2017

Multipath TCP (MPTCP) is a transport layer protocol that simultaneously transmits data using multiple interfaces. MPTCP is superior to existing TCP in network environment with homogeneous subflows, but it shows worse performance compared to existing TCP in network environment with bufferbloat. If a bufferbloat occurs in one of the MPTCP multipaths, the packet will not arrive at the MPTCP receive buffer due to a sudden increase in delay time, resulting in a HoL blocking phenomenon. It makes the receive window of the other path to be zero. In this paper, we apply Adaptive Random Early Detection (ARED), Controlled Delay (CoDel) and Proportional Integral Controller Enhanced (PIE) among the proposed Active Queue Management (AQM) to limit the delay of bufferbloat path. Experiments were conducted to improve the performance of MPTCP in heterogeneous networks. In order to carry out the experiment, we constructed a Linux-based testbed and compared the MPTCP performance with that of the existing droptail.

• Journal of Soil and Groundwater Environment
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• v.19 no.3
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• pp.123-133
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• 2014

It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3150-3163
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• 2023

To improve the performance of blanket: maximizing the tritium breeding rate (TBR) for tritium self-sufficiency, and minimizing the Dose of backplate for radiation protection, most previous studies are based on manual corrections to adjust the blanket structure to achieve optimization design, but it is difficult to find an optimal structure and tends to be trapped by local optimizations as it involves multiphysics field design, which is also inefficient and time-consuming process. The artificial intelligence (AI) maybe is a potential method for the optimization design of the blanket. So, this paper aims to develop an intelligent optimization method based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network to solve these problems mentioned above. This method has been applied on optimizing the radial arrangement of a conceptual design of CFETR HCSB blanket. Finally, a series of optimal radial arrangements are obtained under the constraints that the temperature of each component of the blanket does not exceed the limit and the radial length remains unchanged, the efficiency of the blanket optimization design is significantly improved. This study will provide a clue and inspiration for the application of artificial intelligence technology in the optimization design of blanket.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.730-737
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• 2016

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load's specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.779-785
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• 2015

Recently, home energy management system (HEMS) for power consumption reduction has been widely used and studied. The HEMS performs electric power consumption control for the indoor electric device connected to the HEMS. However, a traditional HEMS is used for passive control method using some particular power saving devices. Disadvantages with this traditional HEMS is that these power saving devices should be newly installed to build HEMS environment instead of existing home appliances. Therefore, an HEMS, which performs with existing home appliances, is needed to prevent additional expenses due to the purchase of state-of-the-art devices. In this paper, an intelligent inference algorithm for EMS at home for non-power saving electronic equipment, called legacy devices, is proposed. The algorithm is based on the adaptive network fuzzy inference system (ANFIS) and has a subsystem that notifies retraining schedule to the ANFIS to increase the inference performance. This paper discusses the overview and the architecture of the system, especially in terms of the retraining schedule. In addition, the comparison results show that the proposed algorithm is more accurate than the classic ANFIS-based EMS system.

• Korean Journal of Hydrosciences
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• v.4
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• pp.1-9
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• 1993

It is a major objective for the management and operation of water resources system to forecast streamflows. The applicability of artificial neural network model to hydrologic system is analyzed and the performance is compared by statistical method with observed. Multi-layered perception was used to model rainfall-runoff process at Pyung Chang River Basin in Korea. The neural network model has the function of learning the process which can be trained with the error backpropagation (EBP) algorithm in two phases; (1) learning phase permits to find the best parameters(weight matrix) between input and output. (2) adaptive phase use the EBP algorithm in order to learn from the provided data. The generalization results have been obtained on forecasting the daily and hourly streamflows by assuming them with the structure of ARMA model. The results show validities in applying to hydrologic forecasting system.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.855-858
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• 1998

Nowadays it is possible to make realization of Multimedia service by virtue of developing computer hardware technique and high-bandwidth network. But Multimedia service has some problems. Its file need large storage. Above all, Analog CCTV used in recent has been utilized for various purpose in ban, company and public institution, but this has many defects such as management, low resolution, and etc. To overcome this problems, multimedia component-file-have to be reduced in size. This paper proposes adaptive MPEG-1 video to reduce file size. The method in this paper is realized that according to movement variation, file size is reduced by adaptively making use of MQuant.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.962-966
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• 2001

The major problem at a branch point for point-to-multipoint available bit rate(ABR) services in asynchronous transfer mode (ATM) networks is how to consolidate backward resource management(BRM) cells from each branch for a multicast connection. In this paper, we propose an efficient feedback consolidation algorithm based on an adaptive dynamic threshold(ADT) to eliminate the consolidation noise and the reduce the consolidation delay. The main idea of the ADT algorithm lies in that each branch point estimates the ABR traffic condition of the network through the virtual queue estimation and the transmission threshold of the queue level in branch points is adaptively controlled according to the estimation. Simulation results show that the proposed ADT algorithm can achieve a faster response in congestion status and a higher link utilization compared with the previous works.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.17-20
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• 2008

A clustering scheme for ad hoc networks is aimed at managing a number of mobile devices by utilizing hierarchical structure of the networks. In order to construct and maintain an effective hierarchical structure in ad hoc networks where mobile devices may move at high mobility, the following requirements must be satisfied. The role of each mobile device for the hierarchical structure is adaptive to dynamic change of the topology of the ad hoc networks. The role of each mobile device should thus change autonomously based on the local information. The overhead for management of the hierarchical structure is small. The number of mobile devices in each cluster should thus be almost equivalent. This paper proposes an adaptive multihop clustering scheme for highly mobile ad hoc networks. The results obtained by extensive simulation experiments show that the proposed scheme does not depend on mobility and node degree of mobile devices in the ad hoc network, which satisfy the above requirements.