• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.669-674
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• 2001

In order to reflect the aggregation situation in the aggregation process, aggregation based on situation assessment (ASA) method was proposed in [1]. It consists of the situation assessment model (SAM) and the ASA algorithm. In the SAM, the value of parameter, p, is transformed into the nearest integer value [1]. The integer-typed output of SAM is used as input for an aggregation. The integer-typed output of SAM indicates the current degree of aggregation situation. The ASA algorithm produces at most finite several aggregation results between min and max. In the sequel, the ASA method can not properly handle the applications with the more sophisticated aggregation results between min and max. In order to solve this problem, we propose two improved ASA (I-ASA) methods. In these I-ASA methods, we allow the value of parameter of SAM to be a real number, and suggest two improved ASA algorithms to make continuous aggregation results between min and max. These I-ASA methods can handle both a precise aggregation and an approximate aggregation. Therefore, when compared to the ASA method [1], the proposed I-ASA methods have advantages in that they can handle the applications with the more sophisticated aggregation results and can be used in the more general applications for aggregations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.209-218
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• 2009

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.342-344
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• 2006

The modem enormous electric power system has made power system analysis much more complex and difficult. For effective analysis of the power system, model reduction and aggregation is required. In this paper, a new aggregation method is presented to aggregate the coherent generators in the large scale power system while matching the power flow. In order to demonstrate the effects of this aggregation method, it is applied to a small scale power system. A multi-variable control technique of $H_{\infty}$ control is also applied to enhance the dynamic stability of the aggregated power system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1367-1372
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• 2007

The modem large electric power system has made power system analysis much more complex and difficult. For effective analysis of the power system, model reduction and aggregation is required. In this paper, a new relation index to identify the coherency among the generators is presented and also a new aggregation method is presented to aggregate the coherent generators in the large scale power system while matching the power flow. In order to demonstrate the effects of this aggregation method, it is applied to the IEEE 39 bus test power system and to the 2006 summer power system of Korea Electric Power Corporation, and the simulation results are compared with those of the original system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.4
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• pp.450-454
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• 1986

In this paper a complexity reduction method in a linear system is studied. The poles to be retained are selected by the dominancy and the values of residues at respective poles. The reduced order model is obtained by the aggregation method, and the aggregation matrix is determined by the eigenvectors of a controllable canonical form. We consider the markov parameter and the time-moment at the same time, thereby getting rid of the steady-state errors. The input-output matrices are obtained using a chained aggregation matrix, and application of this method is illustrated by example.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.35-40
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• 2011

In this paper, we compare and analyze data aggregation methods based on event area in wireless sensor networks. Data aggregation methods consist of two methods: the direct transmission method and the aggregation node method. The direct aggregation method has some problems that are data redundancy and increasing network traffic as all nodes transmit own data to neighbor nodes regardless of same data. On the other hand the aggregation node method which aggregate neighbor's data can prevent the data redundancy and reduce the data. This method is based on location of nodes. This means that the aggregation node can be selected the nearest node from a sink or the centered node of event area. So, we describe the benefits of data aggregation methods that make up for the weak points of direct data dissemination of sensor nodes. We measure energy consumption of the existing ways on data aggregation selection by increasing event area. To achieve this, we calculated the distance between an event node and the aggregation node and the distance between the aggregation node and a sink node. And we defined the equations for distance. Using these equations with energy model for sensor networks, we could find the energy consumption of each method.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.215-229
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• 2005

In this paper, constraint aggregation is combined with the adjoint and multiple shooting strategies for optimal control of differential algebraic equations (DAE) systems. The approach retains the inherent parallelism of the conventional multiple shooting method, while also being much more efficient for large scale problems. Constraint aggregation is employed to reduce the number of nonlinear continuity constraints in each multiple shooting interval, and its derivatives are computed by the adjoint DAE solver DASPKADJOINT together with ADIFOR and TAMC, the automatic differentiation software for forward and reverse mode, respectively. Numerical experiments demonstrate the effectiveness of the approach.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2584-2590
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• 1998

In the existing fuzzy aggregation method, the operators such as t-norm, t conorm, mean operator, Yafer's operator and $\gamma$ operator are used to aggregate the values of membership functions. However, these methods have problems in that they do not reflect the decision situation properlyin the decision process. In order to solve these problems we suggest a situation assessment model(SAM) to reflect the decision situation in the decision proess. In the fuzzy decision environment, we propose a new aggregation method to reflect the decision situation using the result of SAM. We call it the aggregation based on situation assessment (ASA) method. It makes the stepwise aggregation with derection according to the decision situation. Moreover, we compare ASA method with the existing aggregation methods.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1556-1563
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• 2004

In this paper, we propose an efficient full mesh topology aggregation method in PNNI networks. The proposed scheme can search multi-links efficiently using the depth priority method based on hop count instead of searching the all links. To do this, we propose a modified line segment algorithm using two line segment method that represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multiple-links aggregation. And we apply it to current full mesh topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crank back rate. The result is that the proposed scheme is better than the current scheme in performance.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.4
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• pp.168-173
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• 2012

The aggregation of group loads, which consists of the linear and the non-linear systems, yields the error involved in the reactive power aggregation, which is greater than the active power aggregation in the component based load modeling. Each individual reactive power in a group load affects the aggregated load different from composition rate. This paper proposes a new method that determines the degree of impacts by adjusting the coefficient of weight factors of each load using the least squares error method. The effectiveness of proposed algorithm is demonstrated by simulating three aggregation cases.