• 한국대기환경학회지
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• 제11권1호
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• pp.15-28
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• 1995

Over the last two decades, air quality models have been developed and used in the United States. Many of these models ate distributed as parts of UNAMAP. These models have been used as useful tools for urban air quality management in Korea. However, when we use these models, many problems could be occured because of their different topographical and meteorological conditions. In the present study it is described that the characteristics about developement of the local scale diffusion models for application to Korea. Also for evaluation purpose of the models, input data requirements such as air pollutant concentrations, emission inventory, meteorological data, and field experiment data, were discussed.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3563-3579
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• 2021

Measured decay heat data of light water reactor (LWR) spent nuclear fuel (SNF) assemblies are adopted to train machine learning (ML) models. The measured data is available for fuel assemblies irradiated in commercial reactors operated in the United States and Sweden. The data comes from calorimetric measurements of discharged pressurized water reactor (PWR) and boiling water reactor (BWR) fuel assemblies. 91 and 171 measurements of PWR and BWR assembly decay heat data are used, respectively. Due to the small size of the measurement dataset, we propose: (i) to use the method of multiple runs (ii) to generate and use synthetic data, as large dataset which has similar statistical characteristics as the original dataset. Three ML models are developed based on Gaussian process (GP), support vector machines (SVM) and neural networks (NN), with four inputs including the fuel assembly averaged enrichment, assembly averaged burnup, initial heavy metal mass, and cooling time after discharge. The outcomes of this work are (i) development of ML models which predict LWR fuel assembly decay heat from the four inputs (ii) generation and application of synthetic data which improves the performance of the ML models (iii) uncertainty analysis of the ML models and their predictions.

• Computers and Concrete
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• 제11권4호
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• pp.337-350
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• 2013

The sensitivity of compressive strength of no-slump concrete to its ingredient materials and proportions, necessitate the use of robust models to guarantee both estimation and generalization features. It was known that the problem of compressive strength prediction owes high degree of complexity and uncertainty due to the variable nature of materials, workmanship quality, etc. Moreover, using the chemical and mineral additives, superimposes the problem's complexity. Traditionally this property of concrete is predicted by conventional linear or nonlinear regression models. In general, these models comprise lower accuracy and in most cases they fail to meet the extrapolation accuracy and generalization requirements. Recently, artificial intelligence-based robust systems have been successfully implemented in this area. In this regard, this paper aims to investigate the use of optimized support vector machine (SVM) to predict the compressive strength of no-slump concrete and compare with optimized neural network (ANN). The results showed that after optimization process, both models are applicable for prediction purposes with similar high-qualities of estimation and generalization norms; however, it was indicated that optimization and modeling with SVM is very rapid than ANN models.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권2호
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• pp.87-95
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• 2015

In this study, we pursue a new direction for system modeling by introducing the concept of granular models, which produce results in the form of information granules (such as intervals, fuzzy sets, and rough sets). We present a rationale and several key motivating arguments behind the use of granular models and discuss their underlying design processes. The development of the granular model includes optimal allocation of information granularity through optimizing the criteria of coverage and specificity. The emergence and construction of granular models of type-2 and type-n (in general) is discussed. It is shown that achieving a suitable coverage-specificity tradeoff (compromise) is essential for developing granular models.

• 한국정보처리학회논문지
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• 제6권8호
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• pp.2088-2097
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• 1999

소프트웨어 도메인모형(Domain Model)으로부터 행위패턴을 식별하고, 개발 시스템의 동적 행위를 구체화한 사용 사례추출 및 구조화로 재사용을 증진시키는 소프트웨어 프레임워크(Framework) 구축방법을 제안한다. 대부분의 소프트웨어 행위모형이 이질적인 개발자의 요구사항이나 의도를 일관성 있게 모형화 하지 못하며, 재개발과 유지보수를 위한 구체적인 활용방안이 마련되어 있지 못하다. 따라서, 행위패턴을 식별하고 시스템에 반응하는 구체적인 기능성 항목인 사용 사례(Use Case)를 구조화하여 개발된 모형의 일관성을 보완하고, 재사용과 유지보수를 하는 재사용 프레임워크를 구축한다. 사용 사례의 구조화를 위해 격자모형(Lattice Model)이 이용되며, 재사용 구성항목을 추출하도록 유도할 수 있는 재사용 프로세스 구조와 세부절차를 소개한다.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.276-283
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• 2024

Currently, the overall tendency for green and sustainable economic development is creating a circular economy. In actuality, agricultural output is currently benefiting greatly from the growth of the circular economy. The creation of a circular economy helps address resource scarcity, save the environment, combat climate change, and increase economic efficiency. Vietnam's economy can grow quickly and sustainably by shifting to a circular economy production model. Comparing prior growth techniques to the digital age and implementing circular economic development connected with high technology will be a fantastic opportunity to boost growth efficiency. In actuality, Vietnam currently has a large number of agricultural circular economy models. These are models: Creating and using gas from waste and wastewater in livestock and farming; model combining cultivation, livestock, and aquaculture; agro-forestry model; garden-forest model; Circular model using agricultural by-products as a catalyst or creating other valuable products; model of moderation, linked to reducing the use of growth hormones, veterinary medications, pesticides, and artificial fertilizers in agriculture and animal husbandry. Unfortunately, there have been few studies and applications of the aforementioned models, which has made it difficult to build the agricultural sector sustainably. In this paper, we outline the current situation and propose solutions to develop a circular economy model in agriculture in Vietnam for sustainable development.

• 콘크리트학회논문집
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• 제11권6호
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• pp.35-46
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• 1999

The steel fiber reinforced concrete may affect substantially to the tension stiffening at post cracking behavior. Even if several tension stiffening models exist, they are for plain and normal strength concrete. Thus, the development of tension stiffening models for steel fibrous high strength RC members are necessary at this time when steel fiber reinforced and high strength concretes are common in use. This paper presents tension stiffening effects from experimental results on direct tension members with the main variables such as concrete strength, concrete cover depth, steel fiber quantity and aspect ratio. The comparison of existing models against experimental results indicated that linear reduced model closely estimated the test results at normal strength level but overestimated at high strength level. Discontinuity stress reduced model underestimated at both strength levels. These existing models were not valid enough in applying at steel fibrous high strength concrete because they couldn't consider the concrete strength nor section area. Thus, new tension stiffening models for high strength and steel fiber reinforced concrete were proposed from the analysis of experimental results, considering concrete strength, rebar diameter, concrete cover depth, and steel fiber reinforcement.

• 한국산학기술학회논문지
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• 제14권5호
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• pp.2465-2473
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• 2013

본 논문은 도시.지역계획 등 공간계획 분야의 계획지원시스템(PSS)을 핵심구성요소인 도시모형(특히, 토지이용-교통 모형 LUTM)과 지리정보시스템(GIS) 기술의 발전과정을 중심으로 검토하고, 지구온난화 등 환경문제를 중심으로 한 계획과정에 대한 시민참여 요구 확대, 인터넷과 모바일을 기반으로 한 IT 기술심화를 주요 특징으로 하는 변화된 계획환경에 대응하여 PSS의 보완 또는 확장 개념으로서 저탄소도시계획지원에 초점을 둔 포털서비스의 구축방향을 제안한다.

• 대한교통학회:학술대회논문집
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• 대한교통학회 2007년도 제57회 학술발표회논문집
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• pp.565-573
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• 2007

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(2)
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• pp.499-504
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• 1996

Current Probabilistic Safety Assessment (PSA) techniques are not usually utilized for day-to-day applications in nuclear power plants. The major reason for this anomaly is the complexity of plant models developed for PSA studies and the multitude of resulting fault trees. This impediment can be overcome by the use of simplified plant models. However, oversimplified models usually result in loss of valuable information and therefore. simplification approaches have to be used judiciously in order to achieve accurate and meaningful results. For this reason. development of an appropriate simplification approach must be performed using extreme caution followed with results verification in sequence as well as system levels. If there are no significant differences between the simplified and the original models, the simplified model can be efficiently used in the application of the PSA. This paper presents a methodology for how to develop a suitable simplification technique and the results of its verification for sample systems and sequences. The results show that the utilization of simplified plant models will significantly reduce the number of fault trees with no significant loss of accuracy.