• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.139-144
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• 2009

As it got through the step of super-high speed internet, mobile and digital convergence, the Ubiquitous Society is being attained gradually. Now, it is being variously spread not only the little ordinaries of communication but also fields of economy and industry. Specially, RFID and Navigation system are being used at home and foreign. These are prospected to give assistances that it brings along the competitive power of nation. But inflection range of RFID and Navigation is localized in the most simplest. This paper proposes system to reflect the individual and special quality using RFID and Navigation and to fit easily changing environment. And we studied to use what kind of information in the special environment. We used Fuzzy Logic and TSP for making the intelligence path searching and guiding system with more information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.779-785
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• 2015

Recently, home energy management system (HEMS) for power consumption reduction has been widely used and studied. The HEMS performs electric power consumption control for the indoor electric device connected to the HEMS. However, a traditional HEMS is used for passive control method using some particular power saving devices. Disadvantages with this traditional HEMS is that these power saving devices should be newly installed to build HEMS environment instead of existing home appliances. Therefore, an HEMS, which performs with existing home appliances, is needed to prevent additional expenses due to the purchase of state-of-the-art devices. In this paper, an intelligent inference algorithm for EMS at home for non-power saving electronic equipment, called legacy devices, is proposed. The algorithm is based on the adaptive network fuzzy inference system (ANFIS) and has a subsystem that notifies retraining schedule to the ANFIS to increase the inference performance. This paper discusses the overview and the architecture of the system, especially in terms of the retraining schedule. In addition, the comparison results show that the proposed algorithm is more accurate than the classic ANFIS-based EMS system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

• Geomechanics and Engineering
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• v.31 no.4
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• pp.339-352
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• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.369-378
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• 2024

The aim of this study is to conduct a comparative study on the sustainability of the public pension. While the mainstream view on the sustainability of the public pension presupposes financial sustainability, the original purpose of guaranteeing retirement income has been overlooked. The sustainability of the public pension needs to consider not only financial sustainability, but also various factors such as demographic structure, labor productivity, industrial structure, life cycle of working households, government spending on public pensions, economic growth, and social consensus. With this awareness of the problem, this study conducted a fuzzy set qualitative comparative study in 44 countries, including Korea. As a result of the analysis, it was found that Korea had high financial sustainability for a single year, but relatively low integration related to social consultation and public pension operation, and adequacy such as the degree of guarantee and linkage with other pension systems was also relatively low. The sustainability of the broader public pension should be emphasized not only for financial sustainability, but also for adequacy and integration.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.121-131
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• 2017

The Fuzzy-analytic hierarchy process (AHP) was adopted as the methodology for this study because it allows for the use qualitative judgments by experts. Based on results of the analysis of the success factors for frozen storage/cold storage warehouses, the facility factor was identified as the most important to consider. This factor had a weight of 0.307, followed by systems and operations, accessibility, and standardization/automation with weights of 0.263, 0.255, and 0.175, respectively. The conclusions and implications of the study are as follows. First, the efficiency of constant temperature and humidity systems and the heat insulation property of buildings need to be enhanced. Second, the efficiency of the operations should be enhanced through the standardization of equipment rather than by standardizing product loading. Finally, since logistics and transportation costs are higher for frozen storage/cold storage warehouses than for general distribution, accessibility needs to be considered as the first priority.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.179-188
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• 2018

In this paper, we analyze accident factors that occur in the unloading of steel cargoes and try to derive priority of importance among factors. The Fuzzy-AHP, which enables hierarchical analysis through pairwise comparison of factors, is used to derive priorities of safety factors to consider when unloading steel cargo. In the top factor analysis results, weights were ranked in order of human factors, safety education, equipment and facilities, and business environment. The purpose of this paper is to contribute to the improvement of the safety consciousness of the field workers and enterprises and to reduce the incidence of accidents in the unloading and unloading operations by deriving the relative importance between the factors. In the future, it is necessary to study the cargoes of other disasters such as container cargo as well as steel cargo.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.169-178
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• 2018

Gyeongin Port has low awareness, insufficient hinterland infrastructures, and lower competitiveness. So, in this study, we conducted Fuzzy-IPA analysis reflecting the recognition of the consignor companies that are using Gyeongin port to suggest present practical improvement measures for the activation of the operation of Gyeongin port hereafter. As a result of the analysis, three factors, that is, cargo loading/unloading/storage costs, port facility fees, and incentive and support were derived as priority investment areas. Three factors, that is, cargo safety, infrastructure equipment, and inland transportation costs were derived as the areas for maintenance strengthening and factors related to cargo handling and service factors were derived as areas for maintenance of the status quo and areas for gradual improvement, respectively. This study is significant in that it analyzed the recognition of the consignor companies that are using Gyeongin port using a quantifying method and suggested realizable measures for activation based on the results of the analysis. In future studies, the frequency of ships' calling at the port and measures to diversify the sea routes should be additionally reflected on the analysis.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.451-461
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• 2002

Differential evolution(DE) has been preyed to be an efficient method for optimizing real-valued multi-modal objective functions. DE's main assets are its conceptual simplicity and ease of use. However, the convergence properties are deeply dependent on the control parameters of DE. This paper proposes an adaptive differential evolution(ADE) method which combines with a variant of DE and an adaptive mechanism of the control parameters. ADE contributes to the robustness and the easy use of the DE without deteriorating the convergence. 12 optimization problems is considered to test ADE. As an application of ADE the paper presents a supervised clustering method for predicting events, what is called, an evolutionary event clustering(EEC). EEC is tested for 4 cases used widely for the validation of data modeling.