• 대한수학회보
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• 제48권4호
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• pp.839-845
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• 2011

In this paper, we consider the cusum of squares test for the dispersion parameter in stochastic differential equation models. It is shown that the test has a limiting distribution of the sup of a Brownian bridge, unaffected by the drift parameter estimation. A simulation result is provided for illustration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1330-1333
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• 2004

The methodology for modeling building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. Mostly, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents the application of neural networks (NN) to model landlord energy consumption of commercial buildings in Singapore. Firstly, a brief background information on NN and its application on the building energy research is provided. Secondly, five commercial buildings with various characteristics were selected for case studies. Monthly mean outdoor dry-bulb temperature ($T_0$), Relative Humidity (RH) and Global Solar Radiation (GSR) are used as network inputs and the landlord monthly energy consumption of the same period is the output. Up to three years monthly data are taken as training data. A forecast has been made for another year for all the five buildings. The performance of the NN analysis was evaluated using coefficient of variance (CV). The results show that NNs is powerful at predicting annual landlord energy consumption with high accuracy.

• Korean Journal of Mathematics
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• 제13권1호
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• pp.19-34
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• 2005

Pricing and hedging strategy for European options of jump-type asset models, which are derived from a stochastic differential equations, are discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제15권4호
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• pp.277-290
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• 2011

We define some multi-type asset models derved from L$\acute{e}$vy proceses which emphasize coefficients of stochastic differential equations. Also these asset models can be represented by Doleance-Dade linear equations derived from jump-type semimartingales which are decomposed by various terms of time basically. For these asset models, we can construct optimal portfolio strategy by using filtered various information at each check time.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제14권4호
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• pp.211-224
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• 2010

We define some asset models which are useful for portfolio construction in various terms of time. Our asset models are geometric jump-diffusions defined by the solutions of stochastic differential equations which are decomposed by various terms of time basically. We also can study pricing and hedging strategy of options in our models roughly.

• Korean Journal of Mathematics
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• 제22권3호
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.

• 한국공간정보시스템학회 논문지
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• 제10권1호
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• pp.1-14
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• 2008

최근 GIS 분야에서 공간 분석이나 군사적 목적을 위해 좀 더 상세하거나 넓은 영역의 공간 데이타를 요구함에 따라 대용량 공간 데이타의 효율적인 검색에 대한 필요성이 증대되고 있다. 이러한 분야에서 공간 데이타 검색에 활용되고 있는 Oracle Spatial이나 ESRI ArcSDE와 같은 기존의 GIS 소프트웨어는 공간 데이타의 안정적인 관리와 다양한 서비스를 위해 많은 기능들을 제공하지만, 저장 구조 및 공간 연산의 복잡성으로 인해 대용량 공간 데이타에 대한 검색이 비효율적이다. 따라서, 본 논문에서는 대용량 공간 데이타의 효율적인 검색을 위한 공간 미들웨어를 개발하였다. 본 논문에서 개발한 공간 미들웨어는 안정적인 공간 데이타의 관리를 위해 상용 DBMS인 Oracle을 데이타 저장소로써 활용하였으며, Oracle에 저장된 대용량 공간 데이타의 효율적인 접근을 위해 OCCI(Oracle C++ Call Interface)를 이용하였다. 또한, 대용량 공간 데이타의 효율적 연산과 검색을 위해 다양한 공간 연산 기법 및 Array Fetch 기법 등을 사용하였다. 마지막으로, 본 논문에서 개발한 공간 미들웨어와 Oracle Spatial 및 ESRI ArcSDE의 검색 성능을 비교함으로써 공간 미들웨어에 대용량 공간 데이타 검색 성능의 우수함을 입증하였다.