• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.572-578
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• 2008

We analyze the search space considered by the previously proposed R-CORE method for learning Bayesian network structures of large scale. Experimental analysis on the search space of the method is also shown. The R-CORE method reduces the search space considered for Bayesian network structures by recursively clustering the random variables and restricting the orders between clusters. We show the R-CORE method has a similar search space with the previous method in the worst case but has a much less search space in the average case. By considering much less search space in the average case, the R-CORE method shows less tendency of overfitting in learning Bayesian network structures compared to the previous method.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.206-211
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• 2011

In this paper, the evolutionary algorithm was specifically formulated for optimization with continuous parameter space. The proposal was motivated by the fact that the genetic algorithms have been most intensively reported for parameter identification problems with continuous search space. The difference of primary characteristics between genetic algorithms and the proposed algorithm, discrete or continuous individual representation has made different areas to which the algorithms should be applied. Results obtained by optimization of some well-known test functions indicate that the proposed algorithm is superior to genetic algorithms in all the performance, computation time and memory usage for continuous search space problems.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.802-816
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• 2021

Purpose: In this paper, we propose a direction of future research and development to be carried out in the passive tracking field by deriving a white space with enhanced search formula of patent analysis. Method: In this paper, we derive a white space by identifying the direction and the flow of technology change and by matrixing the object and solution through extensive patent search with enhanced search formula and analysis in the field of passive tracking technology. Result: By the proposed scheme, 'multi-target positioning and tracking' and '3D positioning technology' using artificial intelligence, adaptive/hybrid positioning technology, and radar/antenna were derived as white space technologies and confirmed with absence of any services or products. Conclusion: The derived white space technologies from this paper are the areas where patent applications are not active and there are not many prior patents, thus it is necessary to secure the rights through more active R&D and patent application activities.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.597-612
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• 2016

This paper presents an optimization process using Harmony Search Algorithm for minimum weight of steel space frames under earthquake effects according to Turkish Earthquake Code (2007) specifications. The optimum designs are carried out by selecting suitable sections from a specified list including W profiles taken from American Institute of Steel Construction (AISC). The stress constraints obeying AISC-Load and Resistance Factor Design (LRFD) specifications, lateral displacement constraints and geometric constraints are considered in the optimum designs. A computer program is coded in MATLAB for the purpose to incorporate with SAP2000 OAPI (Open Application Programming Interface) to perform structural analysis of the frames under earthquake loads. Three different steel space frames are carried out for four different seismic earthquake zones defined in Turkish Earthquake Code (2007). Results obtained from the examples show the applicability and robustness of the method.

• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.575-588
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• 2007

In this paper, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search. The first algorithm utilizes the features of short-term memory (tabu list) facility and aspiration criteria and the other has long-term memory (back-tracking) facility in addition to the aforementioned features. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Allowable stress design (ASD) specification, maximum drift (lateral displacement) and interstorey drift constraints were imposed on the frames. The algorithms were applied to the optimum design of three space frame structures. The designs obtained using the two algorithms were compared to each other. The comparisons showed that the second algorithm resulted in lighter frames.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Korean Institute of Interior Design Journal
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• v.23 no.3
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• pp.117-124
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• 2014

This study has inferred the mechanism of psychological observation activities through comparison analysis of the observation data acquired from eye-tracking and their post-estimation. The results of their analysis can be summarized as the followings. First, even though the frame of analysis has been set up so that there might not be any change to the number of the sections even with any change of consecutive observation times, the fact that the time by area decreases along with the change of consecutive observation from three times to six and nine times means that the time spent on "recognition" of space information reduces in the course that the feature of observing for space information switches from "perception to recognition". Second, the subjects moves their eyes incessantly in order to acquire space information while observing the space, when it was confirmed that there was a difference between "the space which the subjects searched for information by means of observation activities" and "that which they thought they observed that remaining in their consciousness". The appreciation of this kind of difference is very significant for the analysis of observation features. Third, the short observation (0.1 second, three times of consecutive observations) is consistent with "Ares I, intensively searched = that marked as having been observed consciously" by 60%, while the long-time observation (0.3 second, 9 times of consecutive observations) had 56%, which was relatively high, of "Area I, searched intensively ${\neq}$ that marked as having been observed consciously", which means that the observation feature seen at the activities of "consciousness : unconsciousness" and "observation : search" had some change in the course of changing from "perception to recognition".

• Korean Institute of Interior Design Journal
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• v.22 no.5
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• pp.152-161
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• 2013

This study is about the visual appreciation by sex with the analysis of time range of observing data which was got through observation experiment with the space of lobby in hospitals. The observation data of the subjects who observed the space include the frequency and time, through which the process of visual appreciation could be evaluated with the definition of the frequency and the time of observation. First, the fact that men had higher frequency of observation than women means the former had more movement than the latter, and another fact of their fewer times can be understood as the time of their staying was shorter. That is, even though the men had more movements of sight, they showed the feature of staying shorter. Second, the rate high and low of observation frequency and times made it possible for observation characteristics to be defined as 'intensive search' 'active search' 'fixed concentration' and 'search wandering.' The definition of understanding this process of visual appreciation can be available for a frame of effective analysis of observation characteristics according to the passage of time. Third, the intense search is the case of 'high frequency' having the feature of high visual appreciation owing to the active visual actions for acquiring information. Men were found to have more intense search which decreased gradually as time passed, while women showed the feature of many times of intense search. Fourth, it was found that with many observation data in a certain range of time the subjects had fixed concentration, where women were found to have repetitive fixed concentration along with the change of observation time while men were seen to have more observation tendency for fixed concentration. Fifth, at the cross tabulation of frequency and times, men had the feature of dispersed visual appreciation while women had more distinction between fixation and movement, which revealed that there is surely the difference between men and women in the process of visual appreciation.