• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.11
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• pp.1297-1304
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• 2014

Love which is one of the emotional of mankind, has been studied in sociology and psychology as a matter of grate concern. In this paper We represent romantic behaviors in the love equation of Romeo and Juliet as time series and phase portraits. Also we analyze the behavior's relation by using time series and phase portraits when external force applied as the third person between Romeo and Juliet.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.793-798
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• 2004

In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1073-1078
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• 2012

In this paper, we propose the MEMS system with Duffing equation to confirm nonlinear features in MEMS system. We also analyze nonlinear phenomena when adding the nonlinear term of another type. As a verification, we confirm chaotic motion by parameter variation through the time series, phase portrait and power spectrum.

• Communications of the Korean Mathematical Society
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• v.10 no.2
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• pp.409-417
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• 1995

We consider the $R^k$-valued $(k \geq 1)$ process ${X_n}$ generated by $X_n + 1 = f(X_n)+e_{n+1}$, where $f(x) = (h(x),x^{(1)},x^{(1)},\cdots,x{(k-1)})'$. We assume that h is a real-valued measuable function on $R^k$ and that $e_n = (e'_n,0,\cdot,0)'$ where ${e'_n}$ are independent and identically distributed random variables. We obtained a practical criteria guaranteeing a given process to be geometrically ergodic. Sufficient condition for transience is also given.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.111-117
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• 2010

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

• Geomechanics and Engineering
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• v.13 no.5
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• pp.845-860
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• 2017

It is very important to study displacement prediction in geotechnical engineering. Nowadays, the grey system method, time series analysis method and artificial neural network method are three main methods. Based on the brief introduction, the three methods are analyzed comprehensively. Their merits and demerits, applied ranges are revealed. To solve the shortcomings of the artificial neural network method, a new prediction method based on new evolutionary neural network is proposed. Finally, through two real engineering applications, the analysis of three main methods and the new evolutionary neural network method all have been verified. The results show that, the grey system method is a kind of exponential approximation to displacement sequence, and time series analysis is linear autoregression approximation, while artificial neural network is nonlinear autoregression approximation. Thus, the grey system method can suitably analyze the sequence, which has the exponential law, the time series method can suitably analyze the random sequence and the neural network method almostly can be applied in any sequences. Moreover, the prediction results of new evolutionary neural network method is the best, and its approximation sequence and the generalization prediction sequence are all coincided with the real displacement sequence well. Thus, the new evolutionary neural network method is an acceptable method to predict the measurement displacements of geotechnical engineering.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.76-82
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• 2004

A robust fuzzy controller is designed to stabilize a class of solvable nonlinear descriptor systems with time-varying delay. First, a new modeling and control method for nonlinear descriptor systems is presented with a fuzzy descriptor model. A sufficient condition for the existence of the fuzzy controller is given in terms of a series of LMIs. Then, a less conservative fuzzy controller design approach is obtained based on the fuzzy rules and weights. This method includes the interactions of the different subsystems into one matrix. The effectiveness of the presented approach and the design procedure of the fuzzy controller are illustrated by way of an example.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.714-722
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• 2002

This paper presents a control algorithm for a 3-phase 4-wire series active Power filter. This control algorithm compensates harmonics, input power factor and neutral line currents which are generated by balanced or unbalanced nonlinear loads. The advantage of this control algorithm is direct extraction of compensation voltage references. Therefore, the calculation time is shortened and the performance of the series active power filter is improved. The compensation principle of the proposed control algorithm is presented in detail. A 3KVA laboratory prototype of the three-phase four-wire series active power filter was built and experiments have been carried out. Experimental results are shown to verify the effectiveness of the proposed control algorithm.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.3-6
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• 2004

In this paper, the problem of identifying a time-varying nonlinear system in an adaptive way was considered, whereby the time-varying second-order Volterra series was employed to model the system and the filtered weighted least squares (FWLS) algorithm was utilized for the fast parameter tracking capability with low computational burden. Finally, the performance of the proposed approach was demonstrated by providing some computer simulation results.