• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.157-163
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• 1998

A neural network structure able to perform the operations of analogue and binary addition is proposed. The network employs Hopfield' model of a neuron with the connection elements specified on the basis of an analysis of the energy function. Simulation using NMOS neurons has shown convergence predominantly to the correct global minima.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.590-600
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• 2008

This paper concerns the development of a designer friendly hull form parameterization and its coupling with advanced global optimization algorithms. As optimization algorithms, we choose the Partial Swarm Optimization(PSO) recently introduced to solve global optimization problems. Most general-purpose optimization softwares used in industrial applications use gradient-based algorithms, mainly due to their convergence properties and computational efficiency when a relatively few number of variables are considered. However, local optimizers have difficulties with local minima and non-connected feasible regions. Because of the increase of computer power and of the development of efficient Global Optimization (GO) methods, in recent years nongradient-based algorithms have attracted much attention. Furthermore, GO methods provide several advantages over local approaches. In the paper, the derivative-based SQP and the GO approach PSO are compared with their relative performances in solving some typical ship design optimization problem focusing on their effectiveness and efficiency.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.104-111
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• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA). From an examination for various noise environment, it is shown that the IMCRA has a fundamental drawback for the noise power estimate at the offset region of continuity speech signals. Espectially, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. To overcome the drawback, we apply the global speech absence probability (GSAP) conditioned on both a priori SNR and a posteriori SNR to the speech detection algorithm of IMCRA. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and a composite measure test, we show that the proposed algorithm yields better results compared to the conventional IMCRA-based scheme under various noise environments. In particular, in the case of babble 5 dB, the proposed method produced a remarkable improvement compared to the IMCRA ( PESQ = 0.026, composite measure = 0.029 ).

• Proceedings of the Korea Concrete Institute Conference
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• 1994.10a
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3703-3709
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• 1999

We propose a new approach to reconstruct the surface shape of an object from a shaded image. We use genetic algorithm instead of gradient descent algorithm which is apt to take to local minima and also proposes genetic representation and suitable genetic operators for manipulating 2-D image. And for more effective execution, we suggest hierarchical process to reconstruct minutely the surface of an object after coarse and global reconstruction. A modified Lambertian illumination model including the distance factor was herein adopted to get more reasonable result and an experiment was performed with synthesized and real images to demonstrate the devised method, of which results show the usefulness of our method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.821-831
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• 2014

Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.451-459
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• 2008

Accurate load modeling is essential for power system static and dynamic analysis. By the nature of the problem of parameter estimation for power system load modeling using actual measurements, multiple local optimal solutions may exist and local methods can be trapped in a local optimal solution giving possibly poor performance. In this paper, Trust-Tech, a novel methodology for global optimization, is applied to tackle the multiple local optimal solutions issue in measurement-based power system load modeling. Multiple sets of parameter values of a composite load model are obtained using Trust-Tech in a deterministic manner. Numerical studies indicate that Trust-Tech along with conventional local methods can be successfully applied to power system load model parameter estimation in measurement-based approaches.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.135-142
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• 2004

The severe frontal crash tests are NCAP with belted occupant at 35mph and FMVSS 208 with unbelted occupant at 25mph, This paper describes the design process of occupant protection systems, airbag and seat belt, under the two tests. In this study, NCAP simulations are performed by Monte Carlo search method and cluster analysis. The Monte Carlo search method is a global optimization technique and requires execution of a series of deterministic analyses, The procedure is as follows. 1) Define the region of interest 2) Perform Monte Carlo simulation with uniform distribution 3) Transform output to obtain points grouped around the local minima 4) Perform cluster analysis to obtain groups that are close to each other 5) Define the several feasible design ranges. The several feasible designs are acquired and checked under FMVSS 208 simulation with unbelted occupant at 25mph.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.27-35
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• 1998

Navigation is a method to direct a mobile robot without collision when traversing the environment. This is to reach a destination without getting lost. In this paper, global and local path planning in fixed obstacle and moving obstacle using genetic algorithm are presented. First, mobile robot searches optimal global path using genetic algorithm without falling into local minima. Then if it finds a unknown obstacle, it searches new path without crashing obstacle. Also if there is a moving obstacle, mobile robot searches new optimal path without colliding with the obstacles. Various simulation results show the proposed algorithm can search a shortest path effectively.