• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.

• International Journal of Contents
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• v.8 no.3
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• pp.1-6
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• 2012

This study establishes a simple Causal Map in order to understand the structure of Social Network Services(SNS). From this, the paper proposes a simulation with drawing Simulation Model and it examines whether a Dunbar Number is available for the emergence of collective intelligence based on an on-line network. Through my analytical research, it turn out both Closed SNS and Open SNS have their own Dunbar Number. However, it appear that Open SNS can expand infinitely as it has a unique property namely weak tie. This implies that it is significant for a system or policy to be developed in order to overcome the problem of Dunbar Number, whereas restricting the extension of a network by considering the Dunbar Number would have a negative impact on emergence of collective intelligence.

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.77-86
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• 2005

[ $IP^2$ ] (IP-based IMT Network Platform) is a ubiquitous platform supporting mobility using two step If address IPha (IP host address) and IPra (IP routing address) - in a backbone network. MN (Mobile Node) in $IP^2$ maintains either Active or Dormant state, which is transferred to Active state through Paging process when communication is required. In this paper, we proposed a Paging method using proxy to resolve the problem of the conventional Paging method which transmits the Paging messages to all cells in LA (Location Area) resulting in the excessive use of network resources. Performanceevaluation of the proposed method using NS-2 showed that the usage of network resources becomes more efficient by reducing paging loads, especially under the condition of increased nodes.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.255-264
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• 2005

In this paper, a practical bushing model is proposed to improve the accuracy of the vehicle dynamic analysis. The results of the rubber bushing are used to develop an empirical bushing model with an artificial neural network. A back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model. Then, a full car dynamic model with artificial neural network bushings is simulated to show the feasibility of the proposed bushing model.

• Ocean and Polar Research
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• v.25 no.spc3
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• pp.347-351
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• 2003

A new approach to reliability analysis of rubble mound breakwater using neural network is proposed. At first, a neural network model which can estimate the stability number of any breakwaters for some design conditions is trained. Then, the neural network model is integrated with Monte Carlo simulation technique in order to calculate probability of failure for the breakwater. The proposed technique is compared with conventional approach using empirical formula.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.8
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• pp.863-869
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• 2015

This study analyzed the offshore plant industry and related regulations such as ISO, IEC, and Norsok Standards to develop an integrated network management system (INMS) capable of both on-site and remote management and configuration of IP-based network equipment in offshore plants. The INMS was designed based on actual specifications and POS plans, and a plan of management was verified through an offshore plant engineering company. Various modules such as PAGA interface modules, CCTV, IP-PBX, and HF-radio communication modules were developed for system implementation. Protocol and data design and screen design were followed by framework development and introduction of the automatic satellite communication function.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.110-118
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• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of ‘NARMAX’ form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.112-120
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• 2003

This paper reports the development work carried out in respect of a proposed application of Neural Network approach for the Korean Next generation Reactor (KNGR) now referred as APR-1400. The emphasis is on establishing the methodology and the approach to be adopted towards realizing this application in the next generation reactors. Keeping in view the advantages and limitation of Artificial Neural Network Approach, the role of ANN has been limited to plant status or to be more precise plant transient monitoring. The simulation work carried out so far and the results obtained shows that artificial neural network approach caters to the requirements of plant status monitoring and qualifies to be incorporated as a part of proposed operator support systems of the referenced nuclear power plant.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.3-7
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• 2005

The structure of $IP^2$(IP based-IMT Network Platform) as ubiquitous platform is three-layered model : Middleware including NCPF(Network Control Platform) and SSPF(Service Support Platform), IP-BB(IP-Backbone), Access network including Sensor network. A mobility management(MM) architecture in NCPF is proposed for $IP^2$. It manages routing information and location information separately. The existing method of multicast control in $IP^2$ is Remote Subscription. But Remote Subscription has problem that should be reconstructed whole Multicast tree when sender moves. To solve this problem, we propose a way to put Multicast Manager in NCPF.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.819-827
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• 2013

Compared to legacy frequency hopping communications, future radio communications are required the secure and high data rate, ad-hoc network communication. In this paper, we have designed the network communication structure on the frequency hopping mode, and analyzed the performance of synchronization on the frequency hopping network radio systems. The design results are shown the initial sync. phase of approximately 9 hops and the traffic packet phase of approximately 30 hops. Also, we have simulated the performance on the communication conditions which are carrier bandwidth of 50kHz, user data rate of 64kbps and OQPSK modulation scheme in AWGN. In the simulation, we analyzed the correlation and the performance of synchronization success. The result of simulation show 99% probability for synchronization success at $E_b/N_o$ -4dB.