• Journal of Ginseng Research
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• v.20 no.1
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• pp.65-71
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• 1996

This study was undertaken to evaluate the automatic decision-making on the grading of 6-year-old fresh ginseng (Panax ginseng C.A. Meyer) by an image analyzer. The best input method for the 6-year-old fresh ginseng was under condition of a low resolution (128u 128 pixel) and illumination direction from bottom to up (light box). It was possible to identify the main root, lateral root, and rhizome of fresh ginseng by application of OPEN process in a function of an image analyzer. Finally, we developed the grade decision-making programs, GinP-1. The fitness rates for the fresh ginseng standards which were classified by experts were 94.6, 80.6, 81.5, and 100.0% for 1st, 2nd, 3rd, and 4th grade of fresh ginseng, respectively, and the total time of decision-making was about 4.3 seconds per one root. The decision-making time was reduced to 0.8 seconds per one root by enhancemeat of the Image analyzer, which was tested by the technical company of the image analyzer,'Carl Zeiss (Germany). As a result of this study, the automatic decision-making on the grade of fresh gin send by image analyzer seems to have high possibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• Journal of Ocean Engineering and Technology
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• v.18 no.5
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• pp.29-35
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• 2004

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is proposed for identifying a global solution, using continuous zooming factors for optimization problems. In order to improve the local fine-tuning of the GA, we introduced a new method whereby the search space is zoomed around the design variable with the best fitness per 100 generation, resulting in an improvement of the convergence. Furthermore, the reliability of the optimized solution is determined based on the theory of probability, and the parameter used for the successive zooming method is optimized. With parameter optimization, we can eliminate the time allocated for deciding parameters used in SZGA. To demonstrate the superiority of the proposed theory, we tested for the minimization of a multiple function, as well as simple functions. After testing, we applied the parameter optimization to a truss problem and wicket gate servomotor optimization. Then, the proposed algorithm identifies a more exact optimum value than the standard genetic algorithm.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.453-458
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• 2001

Pipelines have the highest capacity and are the safest and the least environmentally disruptive way for gas or oil transmission. Recently, failures due to corrosion defects have become of major concern in maintaining pipeline integrity. A number of solutions have been developed for the assessment of remaining strength of corroded pipelines. However, these solutions are known to be dependent on material properties and pipeline geometries. In this paper, a Fitness-For-Purpose type limit load solution for corroded gas pipelines made of the X65 steel is proposed. For this purpose, a series of burst tests with various types of corrosion defects are performed. Finite element simulations are carried out to derive an appropriate failure criterion. And then, further, extensive finite element analyses are performed to obtain the FFP type limit load solution for corroded X65 gas pipelines as a function of defect depth, length and pipeline geometry. And also, a window based computer program far the assessment of corrosion defect, which is named as COPAP(COrroded Pipeline Assessment Program) has been developed on the basis of proposed limit load solution.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.423-431
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• 2000

This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.38-43
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• 2008

As the sensibility engineering has become a mainstream information tool, searching answers has become crucial as well. Because the collaborative filtering refers to partial users information who have the similar preference, it tends to ignore the rest. In this paper, we propose the human sensibility ergonomic apparel coordination supporting method using the genetic algorithm. This proposed method calculates evaluation values using fitness function based the genetic algorithm, and gathers through a-cut. To estimate the performance, the suggested method is compared with the existing methods in the questionnaire dataset. The results have shown that the proposed method significantly outperforms the accuracy than the previous methods.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.398-405
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• 2016

A shape of loop-pipe in a compressor affects the vibration of compressor. In this paper, optimal design of shape of loop-pipe to decrease the stress was carried out. Body and shell were assumed to be rigid, while loop-pipe is considered to be flexible. The finite element model was derived and programmed. Genetic algorithm was used for optimization. Locations of 18 point in loop-pipe were considered as shape variables, while the shapes of loop-pipe were interpolated as polynomials or ellipses. Maximum stress of loop-pipe was used as a fitness function for optimization. The spatial constraints and acceleration response of shell were also considered in optimization. The maximum stress and acceleration could be reduced by 79 % and 49 % respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.215-236
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• 2017

Obtaining accurate location information is important in practical applications of wireless sensor networks (WSNs). The distance vector hop (DV-Hop) is a frequently-used range-free localization algorithm in WSNs, but it has low localization accuracy. Moreover, despite various improvements to DV-Hop-based localization algorithms, maintaining a balance between high localization accuracy and good stability and convergence is still a challenge. To overcome these shortcomings, we proposed an improved DV-Hop localization algorithm based on the bat algorithm (IBDV-Hop) for WSNs. The IBDV-Hop algorithm incorporates optimization methods that enhance the accuracy of the average hop distance and fitness function. We also introduce a nonlinear dynamic inertial weight strategy to extend the global search scope and increase the local search accuracy. Moreover, we develop an updated solutions strategy that avoids premature convergence by the IBDV-Hop algorithm. Both theoretical analysis and simulation results show that the IBDV-Hop algorithm achieves higher localization accuracy than the original DV-Hop algorithm and other improved algorithms. The IBDV-Hop algorithm also exhibits good stability, search capability and convergence, and it requires little additional time complexity and energy consumption.