• Bulletin of the Korean Mathematical Society
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• v.48 no.4
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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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• 2004.08a
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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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• v.13 no.1
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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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• v.15 no.4
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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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• v.14 no.4
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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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• v.22 no.3
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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.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.1-14
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• 2008

Recently, because of the need to wide-area spatial data for spatlal analysis and military purpose, there are increasing demand for the efficient retrieval of mass spatial data in Geographic Information System(GIS) fields. Oracle Spatial and ESRI ArcSDE, that are GIS Software, are to manage mass spatial data stably and to support various services but they are inefficient to retrieve mass spatial data because of the complexity of their spatial data models and spatial operations. Therefore, in this paper, we developed a spatial middleware that can retrieve mass spatial data efficiently. The spatial middleware used Oracle which is a representative commercial DBMS as a repository for the stable management of spatial data and utilized OCCI(Oracle C++ Call Interface) for the efficient access of mass spatial data in Oracle. In addition, various spatial operating methods and the Array Fetch method were used in the spatial middleware to perform efficient spatial operations and retrieval of mass spatial data in Oracle, respectively. Finally, by comparing the spatial middleware with Oracle Spatial and ESRI ArcSDE through the performance evaluation, we proved its excellent retrieval and storage performance of mass spatial data.