• The Journal of Fisheries Business Administration
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• v.39 no.3
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• pp.25-47
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• 2008

The Fishing Communities (so-called Uchongae) in Korea was legally established in 1962. It has been gradually expanded by quantity, and we have total 1,969 communities in 2006. The major establishment purpose of Uchongae was put 2 functions. The first function is to make up the double industry structure in coastal region, and second function is to make economical condition for Uchongae. Nevertheless the Fishing Communities System in Korea was not successfully developed after first beginning. The Income gap have become heavily between fishing area and non - fishing area, including agricultural area. The income gap has been due to rapid industrialization and urbanization in Korea. And the income gap even have become heavily among Uchongaes. In this paper, It have been researched the degree of Income inequality among Uchongaes in Korea during 1986-2006. The income inequality degree was analyzed by Gini coefficient and Mean Log Deviation (MLD) using Lorenz Curve. According to analysis result, the Gini coefficient of Uchongaes in Korea has been about 2-times high from 0.0847 to 0.1770 during 20 years. And the MLD has been 5.4 times from 0.0125 to 0.0679 during same periods. This means to more wide the general Income Inequality among the Uchongaes in Korea. Especially, It means to more wide the gap of high ranking Uchongaes and low ranking Uchongaes that MLD index multiplier has been more high.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.453-456
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• 1996

In this paper, the direct adaptive control using neural networks is presented for the control of chaotic nonlinear systems. The direct adaptive control method has an advantage that the additional system identification procedure is not necessary. In order to evaluate the performance of our controller design method, two direct adaptive control methods are applied to a Duffing's equation and a Lorenz equation which are continuous-time chaotic systems. Our simulation results show the effectiveness of the controllers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.236-241
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• 2007

This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.569-571
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• 1998

In this paper, a new method of conrolling chaotic nonlinear systems is proposed. Firstly, the dynamics of a chaotic nonlinear system is separated into a linear part and a nonlinear part. Secondly, the nonlinear part is approximated using a radial basis function network (RBFN) and canceled from the controlled system. Then, the resulting system has only the linear part added with very weak nonlinearity. Finally, a simple linear state feedback control law is designed for the linear part. In the meanwhile, a theorem justifying this concept is presented and proved. Comparing with the feedback linearization, the proposed method can be applied regardless of the functional form of the controlled dynamics. The proposed method is applied by simulation to the Duffing system and the Lorenz system and satisfactory results are obtained.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1041-1044
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• 1999

In This paper, we investigated the single step prediction for output responses of chaotic system with multi Input multi output using chaotic neural networks. Since the systems with chaotic characteristics are coupled between internal parameters, the chaotic neural networks is very suitable for output response prediction of chaotic system. To evaluate the performance of the proposed neural network predictor, we adopt for Lorenz attractor with chaotic responses and compare the results with recurrent neural networks. The results demonstrated superior performance on convergence and computation time than the predictor using recurrent neural networks. And we could also see good predictive capability of chaotic neural network predictor.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.62-66
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• 1996

In this paper, we consider a signal masking structure based on the Lorenz system, which uses a feedback path of the information signal in the transmitter system. The scheme recovers the information signal exactly at the receiver, and can be used with increased amplitude information signal. The scrambling property of the scheme is also investigated by computer simulations, from which the performance is show to be better than that of the conventional method.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.33-44
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• 2020

The main objective of this study is to measure the concentration and deconcentration of the domestic freight forwarding system which illustrate the development trends in this industry. In this study, Herfindal-Hirschman index (HHI), shift-share analysis (SSA), and GINI coefficient combined with Lorenz curves were employed to investigate the domestic freight forwarders. The results are as follows: first, the HHI was used to assess the concentration of domestic freight forwarders in Vietnam. The downward trend from 0.117 in 2008 to 0.083 in 2018 indicate the deconcentration of domestic freight forwarders in Vietnam. Second, the SSA results indicated that the company Transimex showed the best performance with a shift effect of million VND 1,906,515 and a ABSGR value of million VND 2,158,232. Third, the GINI index go down from 0.468 to 0.393 in 2008-2018 as follow and the Lorenz curves covered a large part which make more demonstrate the deconcentration trend of freight forwarding in Vietnam. The results show that deconcentration is a trend in 2008-2018. The results of this study provides relevant data on freight forwarders which are not easily accessible to related stakeholders.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.51-65
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• 2002

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.49-54
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• 2018

Russia has access to unique port locations and routes, one of them is North Sea route, which have been a major debate topic for last several decades. In order to handle any shipments along the route, an adequate and capable port system must be present. This study aims to identify development and competition patterns from 2007 to 2016 of Russian ports in the Arctic basin, concentration trends in particular. The objectives achieved through utilizing the Herfindahl-Hirschman Index (HHI), concentration ratio (CR), the Gini coefficient and Lorenz curve, and shift-share analysis. Results demonstrate concentration trend, positive overall growth and lack of real competition. Originality of this study lies in the fact that certain analysis had not been done in previous studies, but importance of it may be found in several papers. Findings of this paper may assist policy-makers, port authorities and other researchers in understanding and further study on the region.