• Steel and Composite Structures
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• v.49 no.6
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• pp.701-711
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• 2023

In order to fully reflect variation characteristics of composite concrete dam health state, the monitoring data is applied to diagnose composite concrete dam health state. Composite concrete dam lesion development to wreckage is a precursor, and its health status can be judged. The monitoring data are generally non-linear and unsteady time series, which contain chaotic information that cannot be characterized. Thus, it could generate huge influence for the construction of monitoring models and the formulation of corresponding health diagnostic indicators. This multi-scale diagnosis process is from point to whole. Chaotic characteristics are often contained in the monitoring data. If chaotic characteristics could be extracted for reflecting concrete dam health state and the corresponding diagnostic indicators will be formulated, the theory and method of diagnosing concrete dam health state can be huge improved. Therefore, the chaotic characteristics of monitoring data are considered. And, the extracting method of the chaotic components is studied from monitoring data based on fuzzy dynamic cross-correlation factor method. Finally, a method is proposed for formulating composite concrete dam health state indicators. This method can effectively distinguish chaotic systems from deterministic systems and reflect the health state of concrete dam in service.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.763-768
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• 2010

Today the light of mankind since the dawn of mankind and that they were living "lives" on the huge influence across space is a dynamic energy. Because of this, when all human beings with the light and you can feel more comfortable with a stable mind to the beauty and the pursuit of happiness is to have instincts. In this paper, a fuzzy control system using a combination of external environmental factors, respectively, the conversion of quantitative uncertainty information into the LED lighting is designed to express algorithms, available in indoor circadian control circuit was designed and fabricated LED. Factor in the external environment temperature, humidity, and light intensity values to the controller through the sensor to accept these values and the optimal values for lighting the fuzzy control algorithm is converted into human emotion to feel comfortable to express through the dimming control LED lighting.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.122-126
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• 2008

Integrating a 3D solid modeler with a general purpose FEM code, an automatic stress intensity factor analysis system of the 3D crack problems has been developed. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated and quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. Finally, the complete finite element(FE) model generated, and a stress analysis is performed. This paper describes the methodologies to realize such functions, and demonstrates the validity of the present system.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.438-448
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• 2005

This paper proposes an adaptive tutoring system that provides learning materials dynamically according to the learners' teaming character and ability. Our system, in which a learning phase and a test phase are linked together, supports the personalized instruction-learning by providing the teaming materials by level in the learning phase according to the teaming ability estimated in the test phase. We design and implement a tutoring system consisted of an evaluation component and a learning component. An evaluation component uses a computerized adaptive test(CAT) based on item response theory to evaluate learners' ability while a learning component employs fuzzy level set theory so that teaming contents are provided to learners according to learners' level.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.103-111
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• 2023

Accurate cost estimation in the early stages of a construction project is critical to the successful execution of the project. In this study, an ANFIS model was presented to predict construction costs in the early stages of a construction project. To increase the usability of the model, open construction cost data was used, and a model using limited information in the early stage of the project was presented. We analyzed existing studies related to ANFIS to identify recent trends, and after reviewing the basic structure of ANFIS, presented an ANFIS model for predicting conceptual construction costs. The variation in prediction performance depending on the type and number of membership functions of the ANFIS model was analyzed, the model with the best performance was presented, and the prediction accuracy of representative machine learning models was compared and analyzed. Through comparing the ANFIS model with other machine learning models, it was found to show equal or better performance, and it is concluded that it can be applied to predicting construction costs in the early stage of a project.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.92-101
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• 2023

To solve the problem of climate change, carbon neutrality has now become a necessity rather than an option. Hydrogen is not only a energy storage that can supplement the intermittent production of renewable energy, but is also considered a good alternative in the field of utilization as it does not emit carbon dioxide after reaction. In order to revitalize hydrogen vehicles, one of the fields of hydrogen utilization, the construction of hydrogen station infrastructure must be preceded. Prioritization of risk factors is necessary for efficient operation and risk assessment of hydrogen stations, but due to the short operation period of domestic hydrogen stations, there is a lack of frequency data on accidents and their reliability is low. In this study, we aim to identify the causes and consequences of deviations in hydrogen stations through HAZOP analysis. Additionally, we intend to analyze them using Fuzzy-AHP. Through this, we intend to derive the decision values for the causes of deviations in hydrogen stations and apply them to hydrogen accident cases and risk assessments to confirm the reliability and utility of the data.

• Journal of Bio-Environment Control
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• v.7 no.4
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• pp.283-289
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• 1998

The adaptability of an evaporative cooling system to hot summer climate in greenhouses was comprehensively judged by fuzzy theory, based on the 20 years(1975~1994) weather data of nine representative regions in Korea. As uses the evaporative cooling system for greenhouses during summer in Korea, the inside air temperature of most regions except the southwest coastal areas, the south coastal areas, and Cheju island can be basically controlled below 32.5$^{\circ}C$, and ventilating air can be cooled 5$^{\circ}C$ and more. The analyzed results in this paper are on the basis of good ventilation system. When the evaporative cooling system is applied, the ventilation system which has good air flow organization is needed. Although the summer climate in Korea is high temperature and humidity, evaporative cooling systems are suitable for farm buildings in most regions. This facts better meet the needs of cooling for greenhouse in summer and provides a scientific basis for spreading the evaporative cooling system It is proposed that the further research is needed about the application of evaporative cooling system to greenhouses.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.11-14
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• 1990

The detection of pulmonary blood vessels is very difficult owing to their complex tree structures and different widths. In this paper, We propose a new detection algorithm. The motivation of this algorithm is that Han is the best detector. So, this algorithm is developed to imitate the human searching process. To realize it, the algorithm consist of two components. One is Pyramid Images whose one pixel is median value of four pixels of the previous low level. Searching gradually from high level to low level, We concentrate on global and main information of structure at the first. Then based on it, We search the detailed data in low level. The other is fuzzy logic which makes it easy to convert searching process expressed as human language into numeric multi_value. This algorithm showes speedy and robust results. But the more study on both human searching process and the detection of small part is needed.

• Journal of radiological science and technology
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• v.25 no.1
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• pp.77-81
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• 2002

The purpose of this study is to examine quantitatively the relationship between visual image quality and degradation In spatial resolution for a gamma camera by the increase in distance from collimator. The relationship between the portion(p) of images identified the difference of image quality and the difference(${\Delta}FWHM$) in FWHM between paired images was showed in a sigmoid curve. Using Dendy's method, minimum level to be correctly identified the difference of Image duality on three out of four occasion(p=0.75) was corresponded to 0.4 mm in ${\Delta}FWHM$. Using fuzzy theory, the level to be identified the difference of image quality was examined under various conditions. The truth-value of fuzzy sets-degraded or slightly degraded and not-degraded in image quality between palled Images-was gained the peak at 0.5 mm of ${\Delta}FWHM$. It was founded that changes of $0.4{\sim}0.5\;mm$ in FWHM-corresponding about 2 cm distance from collimator could be sufficiently identified in the difference of image quality.