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재해가 발생하기 전에 재해의 규모와 이에 따른 영향 및 피해액을 신속하게 추정하는 것 은 효율적인 재난관리를 하는데 있어 중요하고, 더불어 정책결정자들이 의사결정을 할 때 도움이 될 수 있다. 하지만 기존의 연구는 재해 발생 후에 그 피해액 혹은 복구액을 산정하 고 있어 재해 발생전에 미리 피해액을 추정하는 연구는 매우 미흡한 실정이다. 따라서 본 연구의 목적은 재해 발생 전에 그 피해규모와 영향을 고려하여 이에 따른 피해 액을 신속하게 추정하기 위해 비선형 회귀식을 이용해 강우-홍수피해액에 대한 함수를 제 시하여 강우에 따른 피해액을 미리 추정할 수 있도록 하고자 하였다. 경기도 3개 지역에 대한 강우-홍수피해액의 비선형 회귀식을 이용한 결과, 수원시 경우 실제 피해액보다 -14.16%, 양평군의 경우 –15.81%, 이천시의 경우 +37.33%로 과소·과대 추정이 되었다. 과소추정의 원인으로는 지역의 재해대응력증가, 자연재해의 불확실성 및 재해 연보의 부정확성으로 볼 수 있으며, 과대추정의 원인으로는 피해액에 대한 자료의 부족, 강 우-홍수피해액간의 낮은 상관성이 원인으로 분석되었다. 이러한 문제점들은 근원적으로 해 결하기 어려운 자연현상의 불확실성과 이에 따른 대응능력 또한 지역별로 다르다는 점이다. 따라서 이러한 부분들을 개선하는 연구가 수행된다면 보다 더 신뢰할 수 있는 결과가 도출 될 것으로 기대된다.

Predicting and estimating the disaster characteristics are very important for disaster planning such as prevention, preparedness, response, and recovery. Especially, if we can predict the flood damage before flooding, the predicted or estimated damage will be a very good information to the decision maker for the response and recovery. However, most of the researches, have been performed for calculating disaster damages only after disasters had already happened and there are few studies that are related to the prediction of the damages before disaster. Therefore, the objective of this study was to predict and estimate the flood damages rapidly considering the damage scale and effect before the flood disaster, For this the relationship of rainfall and damage had been suggested using nonlinear regression equation so that it is able to predict the damages according to rainfall. We compared the estimated damages and the actual ones. As a result, the damages were underestimated in 14.16% for Suwon-city and 15.81% for Yangpyeong-town but the damage was overestimated in 37.33% for Icheon-city. The underestimated and overestimated results could be occurred due to the uncertainties involved in natural phenomenon and no considerations of the 4 disaster steps such as prevention, preparedness, response, and recovery which were already performed.. Therefore, we may need the continuous study in this area for reducing various uncertainties and considering various factors related to disasters.

재해가 발생하기 전에 피해규모와 이에 따른 영향 및 피해액을 신속하게 추정하는 것은 효율적인 재난 관리를 하는데 있어 중요하고, 더불어 정책결정자들이 의사결정을 할 때 도움이 될 수 있다. 하지만 기존의 연구는 단순 재해 피해발생 후에 그 피해액 혹은 복구액을 산정하는 수준이며, 현재 피해액 추정에 대한 연구는 전무 하며 그 기술개발에 또한 초기단계에 있다. 이에 피해액 추정에 대한 연구가 시급한 실정이다. 실질적으로 자연재해 정보에 대한 수요가 급증하고 있는 반면에 체계적이고 일관된 통계기반의 정보체계는 미흡하다. 이에 국가에서도 재해에 대한 피해액 및 복구비 산정 등 예산편성에 있어 큰 어려움을 겪고 있 다. 기존통계 방식에 대한 개선의 필요성 인식과 더불어 본 연구의 목적은 재해 발생 전에 그 피해규모와 영향을 고려하여 이에 따른 피해액을 신속하게 추정하기 위함에 있다. 본 연구에서는 비선형 회귀식을 이 용하여 강우-홍수피해액에 대한 함수를 제시하고자 한다.

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문 제에 대하여 연구 하였다. 소프트웨어의 결함을 제거하거나 수정 작업과정에서 유한고장수를 가진 비동질적인 포아송 과정에 기초하였다. 수명강도는 다양한 형상모수와 척도모수에 이용 할 수 있기 때문에 신뢰성 분야에서 많이 사용되 는 비선형 특성을 가진 반-로지스틱 분포 모형을 이용한 방출시기에 관한 문제를 제시하였다. 소프트웨어 요구 신뢰 도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 최적 소프트웨어 방출 정책에 대하여 논의 되었 다. 본 논문의 수치적인 예에서는 고장 시간 자료를 적용하였으며 모수추정 방법은 최우추정법을 이용하고 최적 방 출시기를 추정하였다. 따라서 소프트웨어 방출시기를 사전 정보로 활용하면 잠재적 보안피해액을 줄 일 수 있다고 판단된다.

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and propose release policies of the life distribution, half-logistic property model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time. Software release time is used as prior information, potential security damages should be reduced.

In this study, a bistable energy harvester (BEH) with a piecewise potential function is proposed to improve its energy harvesting performance. A mathematical model of the piecewise BEH (PWBEH) system is established first and a series of numerical simulation are performed, based on the developed model, in order to investigate the nonlinear dynamic behaviors and energy-harvesting performance of the system. The analysis results for the proposed PWBEH system are compared with a conventional BEH (CBEH). The frequency response results show the stiffness-softening interwell motion of the PWBEH, due to the piecewise potential energy function, which is contrary to the stiffness-hardening behavior of the CBEH. Such softening behavior of interwell motion tends to reduce the operating frequency of the BEH, while significantly increasing the output power. This observation indicate that the introduction of the piecewise potential function to a BEH would be beneficial to the system design for enhancing enegy-harvesting performance at the cost of redundant frequency band, which depends on the characteristics of environmental vibration sources.

A kind of adaptive synchronous control method was proposed to solve a special synchronization problem between two chaotic systems, where the response system is totally known without uncertainty but the driven system contains both unknown parameters and uncertain nonlinear functions. An update law of estimation of unknown parameters of driven system by constructing a proper Lyapunov energy function and the stability of the whole system was guaranteed by Lyapunov stability theorem. What is worthy pointing out is that the chaotic systems are not required to satisfy the Lipscitz condition. At last, detailed numerical situation was done to show the rightness and effectiveness of the proposed method.

본 논문에서는 오차 신호의 비선형 함수를 이용하는 VS-CCA (Varying Step-Compact Constellation Algorithm)에서 적응을 위한 step 변화 속도값에 따른 적응 등화의 성능을 비교하였다. VS-CCA 알고리즘은 16-QAM 과 같은 nonconstant modulus 신호를 4개의 4-QAM constant modulus 신호군으로 compact화한 후, 송신 신호 의 통계치인 고정 modulus를 이용하여 오차 신호를 발생하여 이의 비선형 함수를 이용하는 varying step으로 최소 비용 함수를 얻도록 적응 등화기의 탭 계수를 갱신한다. 이때 비선형 함수의 step 변화 속도값에 따라 순시 적응 step값 이 결정되며, 이의 값에 따라 상이한 적응 등화 성능을 얻을 수 있음을 컴퓨터 시뮬레이션을 통해 확인하였다. step 변화 속도값에 따른 등화 성능 비교 지수로는 등화기 내부 지수와 외부 잡음에 대한 강인성을 나타내는 등화기 외부 지수를 사용하였다. 컴퓨터 시뮬레이션 결과 정상 상태에서 변화 속도를 1.0보다 적게 할수록 모든 성능 지수에서 1.0보다 큰 경우 보다 우월해짐을 알 수 있었다.

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

In this paper, a fuzzy-neural interpolating network is proposed to efficiently approximate a nonlinear function. Specifically, basis functions are first constructed by Fuzzy Membership Function based Neural Networks (FMFNN). And the fuzzy similarity, which is defined as the degree of matching between actual output value and the output of each basis function, is employed to determine initial weighting of the proposed network. Then the weightings are updated in such a way that square of the error is minimized. To show the capability of function approximation of the proposed fuzzy-neural interpolating network, a numerical example is illustrated.

In this paper, genetic algorithm (GA) is the technique to search for the optimal structures (i,e., the kind of neural network, the number of hidden neuron, ..) of the neural networks which are used approximating a given nonlinear function, In this paper, we used multi layer feed-forward neural network. The decision method of synapse weights of each neuron in each generation used back-propagation method. In this study, we simulated nonlinear function approximation in the temperature control system.

A new 2-D block Kalman filtering method which uses a nonlinear function is presented to generate a more accurate filtered estimate of a range image that has been corrupted by additive noise. Novel 2-D block Kalman filtering method is constructed of the conventional method and nonlinear function which utilizes to control estimation error. We show that novel 2-D Kalman filtering method using a nonlinear function is effective at reducing the additive noise, not distorting shape edges.

In this paper, a CNN using 1-dimensional chaos circuits with controllable nonlinear functions is proposed. The proposed CNN consists of $\p{times}q$ chaos circuits which are called cell circuits. The nonlinear functions of the cell circuits can be controlled by employing fuzzy scheme. Thanks to the controllability of the nonlinear functions, the proposed circuit can adjust transition behavior of the CNN electronically. Furthermore, the chaotic behavior of the cell circuit which is a portion of the proposed CNN is simple since the cell circuit is a 1-dimensional chaos circuit. To confirm the validity of the circuit design, SPICE simulations were performed concerning the proposed CNN.

Iris recognition system is the one of the most reliable biometries recognition system. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transformed into polar coordinates. After performing three times Wavelet transformation, normalization was done using a sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compared pairs of two adjacent pixels. The binary code of the iris is transmitted to the server by the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the database. The process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

The nonlinear analytic function expansion nodal (AFEN) method is applied to the solution of the time-dependent neutron diffusion equation. Since the AFEN method requires both the particular solution and the homogeneous solution to the transient fixed source problem, the derivation solution method is focused on finding the particular solution efficiently. To avoid complicated particular solutions, the source distribution is approximated by quadratic polynomials and the transient source is constructed such that the error due to the quadratic approximation is minimized. In addition, this paper presents a new two-node solution scheme that is derived by imposing the constraint of current continuity at the interface corner points. The method is verified through a series of applications to the NEACRP PWR rod ejection benchmark problem.

Electric Power system is a large scale nonlinear control one. Therefore, nonlinear control is desirable for the stabilizing, and it is thought that to establish an analytical method for optimal control inputs of AVR(automatic voltage regulator) and GOV(governor) is an important subject. In this paper, as a simple case, one-machine infinite-bus electric power model system with GOV is treated under the three kinds of control inputs; (i) fuzzy control input, (ii) linear control input and (iii) no control input. Next, the stability for each case is analyzed, and the three-dimensional stability regions and control responses are evaluated and compared. Finally, it is concluded that the linear control input does not necessarily give a good region and response, and the fuzzy one is better than others.

The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

자기상관함수는 수문시계열의 선형상관 관계를 나타내는 척도롤 널리 이용되고 있다. 그러나 비선형 동역학에서 필수적인 지체시간 또는 무상관시간 $\tau$d를 산정하는데는 적합하지 않을수도 있기 때문에 비선형 상관관계의 척도로 상호정보이론이 추천되어 왔다. 최근에 일부 학자들은 카오스 동역학 분석을 위하여 지체신간 $\tau$d대신에 상태 공간상에 구축된 각 상태 벡타점 성분들의 총시간을 표시하는 지체시간창을 제안하였다. 그러나 지체신간창은 자기상관함수나 상호정보이론에 의해 추정될 수 없다. 기본적으로 지체신간창은 시계열 자료의 상관관계가 가장 작을 최적시간이며 지체시간은 국지적인 최소값 중 첫 번째의 최적시간이다. 본 연구에서는 수문시계열의 지체시간과 지체사간창을 구하기 위하여 C-C밥법이라는 기법을 이용하고, 여기에서 산정된 값들을 근거로 수문시계열의 모형화와 예측에 중요한 선형 또는 비선형 종속성을 파악하고자 한다.

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

We consider obtaining graphical summaries of uncertainty in estimates of parameters in nonlinear models. A nonlinear constrained optimization algorithm is developed for likelihood based confidence intervals for the functions of parameters in the model The results are applied to the problem of finding significance levels in nonlinear models.

In this paper, a system of nonsmooth equations reformulated from a nonlinear complementarity problem with nonsmooth data is studied. The formulas of some subdifferentials for related functions in this system of nonsmooth equations are developed. The present work can be applied to Newton methods for solving this kind of nonlinear complementarity problem.

This paper addresses the problem of designing robust adaptive output tracking control for a class of MIMO nonlinear systems which have different number of inputs and outputs The stability of the whole closed-loop system is guaranteed in the sense of Lyapunov and uniformly Itimately boundedness of the tracking error vector as well as estimated parameters are shown. In addition, we show that the restrictive assumptions on input gain matrix which is presumed in the past works can be eliminated by using proposed control law.