• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.11
• /
• pp.2108-2116
• /
• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• Journal of muscle and joint health
• /
• v.16 no.2
• /
• pp.116-124
• /
• 2009

Purpose: The purpose of this study was to examine the effects of a Tai Chi exercise program on physical function and physiological variables in patients with degenerative arthritis. Methods: The study utilized a nonequivalent control group with pretest-posttest design. Data collection was done with the elders from two welfare institutions in C-city between July I and September 22, 2007. The participants were assigned either to an experimental group (n=24) or to a control group (n=22). The experimental group participated in Tai Chi exercise for 60 minutes per session, twice a week for 12 weeks and the control group received the education about arthritis for 3 weeks. Results: Except for $VO_2max$, weight, and body fat rate, the elders in the experimental group showed significant improvement in physical function (grip strength, flexibility, balance), and physiological variables (BP) compared to the control group. Conclusion: The results suggest that Tai Chi exercise would partially improve physical function, and physiological variables. Further studies are needed to determine the effects on physical fitness and physiological variables after Tai Chi exercise in this population.

• Water for future
• /
• v.7 no.2
• /
• pp.107-111
• /
• 1974

Annual runoff in the Nakdong river basin has been analyzed to find the probability functions of best fit to distribution of historical annual runoff. The results obtained are as follows; (1) Log-normal 3-parameter disrtibution is believed as the probability function of best fit to historical distribution (2) Log-normal 3-parameter disrtibution is believed as the best fit probability function among Log-normal dist-ributions. (3) In the test of goodness of fit, $x^2-test$ shows that probability of $x^2-valus$ in Log-normal 3-parameter distribution is nearly more than 90%. But in the Simirnov-Kolmogorov test, hypotheses for the probability distributions cannot be rejected at significance level 5% & 1%. (4) Among 7 gauging stations, Dongchon & Koryung-Bridge's records show lower fitness to the theoretical probability functions than other 5 gauging station's

• Korean Management Science Review
• /
• v.29 no.3
• /
• pp.107-120
• /
• 2012

In this paper we propose an effective genetic algorithm for solving the integrated inventory and routing problem of supply chain composed of multi-warehouses and multi-retailers. Unlike extant studies dealing with integrated inventory and routing problem of supply chain, our model incorporates more realistic aspect such as positive inventory at the multi-warehouses under the assumption of inventory policy of power of two-replenishment-cycle. The objective is to determine replenishment intervals for the retailers and warehouses as well as the vehicles routes so that the total cost of delivery and inventory cost is minimized. A notable feature of our algorithm is that the procedure for evaluating the fitness of objective function has the computational complexity closing to linear function. Computational results show effectiveness of our algorithm.

• ETRI Journal
• /
• v.34 no.5
• /
• pp.696-705
• /
• 2012

Accurate synthesis models based on artificial neural networks (ANNs) are proposed to directly obtain the physical dimensions of an asymmetric coplanar waveguide with conductor backing and substrate overlaying (ACPWCBSO). First, the ACPWCBSO is analyzed with the conformal mapping technique (CMT) to obtain the training data. Then, a modified genetic-algorithm-Levenberg-Marquardt (GA-LM) algorithm is adopted to train ANNs. In the algorithm, the maximal relative error (MRE) is used as the fitness function of the chromosomes to guarantee that the MRE is small, while the mean square error is used as the error function in LM training to ensure that the average relative error is small. The MRE of ANNs trained with the modified GA-LM algorithm is less than 8.1%, which is smaller than those trained with the existing GA-LM algorithm and the LM algorithm (greater than 15%). Lastly, the ANN synthesis models are validated by the CMT analysis, electromagnetic simulation, and measurements.

• International Commerce and Information Review
• /
• v.10 no.1
• /
• pp.329-347
• /
• 2008

The purpose of this study is to examine the causal relationship between the exchange rate and economic growth, and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply Granger causality based on an error correction model. The results indicate that uni-dierctional causality between exchange rate and economic growth is detected. Exchange rate impacts on economic growth, but economic growth don't impact on exchange rate. The analysis of impulse reaction function shows that the impulse of exchange rate impacts on Korean economic growth in negative direction. We can infer policy suggestion as follows: The fluctuation of exchange rate much affects economic growth, thus we must make a stable policy of exchange rate to continue economic growth.

• International Journal of Aeronautical and Space Sciences
• /
• v.7 no.1
• /
• pp.1-12
• /
• 2006

In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).

• Journal of KIISE:Software and Applications
• /
• v.32 no.1
• /
• pp.62-73
• /
• 2005

Evolvable Hardware is the technique that obtains target function by adapting reconfigurable digital' devices to environment in real time using evolutionary computation. It opens the possibility of automatic design of hardware circuits but still has the limitation to produce complex circuits. In this paper, we have analyzed the fitness landscape of evolvable hardware and proposed a speciation technique of evolving diverse individuals simultaneously, proving the efficiency empirically. Also, we show that useful extra functions can be obtained by analyzing diverse circuits from the speciation technique.

• Journal of Welding and Joining
• /
• v.29 no.6
• /
• pp.82-87
• /
• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.869-874
• /
• 2005

This paper proposes the Pareto artificial life algorithm for a multi-objective function optimization problem. The artificial life algorithm for a single objective function optimization problem is improved through incorporating the new method to estimate the fitness value fur a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm is applied to the optimum design of a Journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application are reported to present the possible solutions to a decision maker or a designer.