• Structural Engineering and Mechanics
• /
• v.55 no.3
• /
• pp.535-554
• /
• 2015

Dolphin echolocation (DE) optimization algorithm is a recently developed meta-heuristic in which echolocation behavior of Dolphins is utilized for seeking a design space. The computational performance of meta-heuristic algorithms is highly dependent to its internal parameters. But the computational time of adjusting these parameters is usually extensive. The DE is an efficient optimization algorithm as it includes few internal parameters compared with other meta-heuristics. In the present paper a modified Dolphin echolocation (MDE) algorithm is proposed for optimization of steel frame structures. In the MDE the step locations are determined using one-dimensional chaotic maps and this improves the convergence behavior of the algorithm. The effectiveness of the proposed MDE algorithm is illustrated in three benchmark steel frame optimization test examples. Results demonstrate the efficiency of the proposed MDE algorithm in finding better solutions compared to standard DE and other existing algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1997.10a
• /
• pp.181-184
• /
• 1997

Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.2
• /
• pp.379-388
• /
• 2000

Previous studies on high impedance faults assumed that the erratic behavior of fault current would be random. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents, which represent geometrical self-similarity are calculated. In addition, qualitative analysis such as phase planes, Poincare maps obtained from fault currents indicate that the irregular behavior is described by strange attractor.

• Publications of The Korean Astronomical Society
• /
• v.7 no.1
• /
• pp.51-61
• /
• 1992

The nonlinear stochastic behavior of chaotic inflation is characterized by the 'scaling' effect. Using a simple criterion for the appearance of scaling behavior in the ${\lambda}{\phi}^4$ inflation model, we show explicitly that in this limit the onset of the scaling regime does not require any special initial conditions and that it is independent of the self-coupling constant ${\lambda}$. Non-Gaussian statistics in adiabatic fluctuations are important only for super-horizon scales and the scaling regime does not lead to any significant statistical properties on currently observable scales. However, the scaling effect gives some cosmological consequences very different from what we expect in the naive diffusion approximation for quantum fluctuations. The classical (deterministic) treatment of the inflation field (essentially a quantum mechanical object.) becomes valid towards the end of inflation.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.1017-1020
• /
• 2000

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.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.5
• /
• pp.545-549
• /
• 1999

Previous studies on high impedance faults assumed that the erratic behavior of fault current would be random. In this paper we prove that the nature of the high impedance faults is indeed a deterministic chaos not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents in order to evaluate the orbital instability peculiar to deterministic chaos dynamically and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. In addition qualitative analysis such a s phase planes Poincare maps obtained from fault currents indicate that the irregular behavior is described by strange attractor.

• Journal of KIISE:Information Networking
• /
• v.31 no.4
• /
• pp.375-383
• /
• 2004

As wireless mobile networks have been widely adopted due to their convenience for deployment, the research for improving their performance has been actively conducted. Since their throughput is restrained by the packet corruption rate not by congestion as in wired networks, however, network simulations for performance evaluation need to select the appropriate wireless channel model representing the behavior of propagation errors for the evaluated channel. The selection of the right model should depend on various factors such as the adopted frequency band, the level of signal power, the existence of obstacles against signal propagation, the sensitivity of protocols to bit errors, and etc. This paper analyzes 10-day bit traces collected from real sensor channels exhibiting the high bit error rate to determine a suitable sensor channel model. For selection, it also evaluates the performance of two error recovery algorithms such as a link layer FEC algorithm and three TCPs (Tahoe, Reno, and Vegas) over several channel models. The comparison analysis shows that CM(Chaotic Map) model predicts 3-time less BER variance and 10-time larger PER(Packet Error Rate) than traces while these differences between the other models and traces are larger than 10-time. The simulation experiments, furthermore, prove that CM model evaluates the performance of these algorithms over sensor channels with the precision at least 10-time more accurate than any other models.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.1
• /
• pp.89-97
• /
• 2008

Chaotic behavior in motor systems is undesired dynamics in real-time implementation since the speed is oscillated in a wide range and the torque is changed by a random manner. We present an adaptive control approach for time-varying permanent-magnet synchronous motors (PMSM) with chaotic phenomenon. We consider that its parameters are changed randomly within certain bounds. First, a nonlinear system model of a PMSM is transformed to derive a nominal linear control strategy. Then, an auxiliary control for compensating real-time control error occurred by system perturbation due to parameter change is designed by using Lyapunov stability theory. Numerical simulation is accomplished for evaluating its efficiency and reliability comparing with the traditional control method. Additionally, we test our control method in real-time motor experiment including a PSoC based drive system to demonstrate its practical applicability.

• Journal of Korean Association for Spatial Structures
• /
• v.14 no.1
• /
• pp.85-91
• /
• 2014

The purpose of this paper is to study comparative of dynamic instability characteristic of Geiger-typed cable dome structures by load condition, which is well-known among the cable dome structures that are the lightweight hybrid structure using compression and tension element continuously. Dynamic buckling process in the phase plane is very important thing for understanding why unstable phenomena are sensitively originated in nonlinear dynamic by various initial conditions. But there is no paper for the dynamic instability of hybrid cable dome by Sinusoidal Excitations, many papers which deal with the dynamic instability for shell-structures under the step load have been published. As a result of Geiger-typed cable dome, which shows chaotic behavior in dynamic nonlinear analysis with initial imperfection.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2000.11a
• /
• pp.43-49
• /
• 2000

Heat transfer characteristics of self oscillating heat pipe were experimentally investigated for the effect of fill charge ratios and heat loads. The heat pipe used for this study is made of copper capillary, has 0.002m internal diameter, a 0.34m length in one turn and consists of 19 turns. Heating and cooling section each have a length of 70mm. Water was used as working fluid inside heat pipe. As the experimental results, the self oscillating heat pipe was operated by self-exited oscillation and circulation of working fluid and the oscillation within the self oscillating heat pipe assumed chaotic behavior.