• 제어로봇시스템학회논문지
• /
• 제8권7호
• /
• pp.556-562
• /
• 2002

This paper studies the identification of a combustion model, which is used to design a linear controller of a steam generation quantity and harmful exhaust gases of a Refuse Incineration Plant(RIP). Even though the RIP has strong nonlinearities and complexities, it is identified as a MIMO parametric ARX model from experimental input-output data sets. Unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. It is shown that the identified model well approximates the input-output combustion characteristics.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.244-244
• /
• 2023

Both the frequency and the magnitude of hydrometeorological extreme events such as severe floods and droughts are increasing. In order to prevent a damage from the climatic disaster, hydrological models are often simulated under various meteorological conditions. While performing the simulations, a synthetic data generated through time series models which maintains the key statistical characteristics of the sample data are widely applied. However, the synthetic data can easily maintains both the average and the variance of the sample data, but the quantile is not maintained well. In this study, we proposes a data generation method which maintains the quantile of the sample data well. The equations of the former maintenance of variance extension (MOVE) are expanded to maintain quantile rather than the average or the variance of the sample data. The equations are derived and the coefficients are determined based on the characteristics of the sample data that we aim to preserve. Monte Carlo simulation is utilized to assess the performance of the proposed data generation method. A time series data (data length of 500) is regarded as the sample data and selected randomly from the sample data to create the data set (data length of 30) for simulation. Data length of the selected data set is expanded from 30 to 500 by using the proposed method. Then, the average, the variance, and the quantile difference between the sample data, and the expanded data are evaluated with relative root mean square error for each simulation. As a result of the simulation, each equation which is designed to maintain the characteristic of data performs well. Moreover, expanded data can preserve the quantile of sample data more precisely than that those expanded through the conventional time series model.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권5호
• /
• pp.487-496
• /
• 2022

This study attempts to discover a differentiated service strategy for the hotpot restaurant industry from the perspective of Chinese Generation Z customers, as well as to further explore the inner needs of Chinese Generation Z to make practical implications for discovering the method of gaining their satisfaction and loyalty. This paper employs questionnaires to collect analytical data and through a case study to produce company strategies. Smith's Marketing Ethics Sequential System Model (SMESSM) is introduced in this paper for the decision of whether the case study company Haidilao Hot Pot should make a new strategy on service based on Generation Z's consuming behavior. The findings of this study demonstrate that hotpot restaurant must differentiate their services for Generation Z from older generation customers to gain a sustainable development of the hotpot business. Proper differentiated service will not only improve Generation Z's dining experience but also reduce costs. This paper is the first to discuss differentiated service strategy in the hotpot restaurant business from the perspective of Generation Z customers. And a Chinese experience of SMESSM for practical use is introduced in this paper, which enriches the relevant implications for future research on business strategy.

• Journal of information and communication convergence engineering
• /
• 제13권2호
• /
• pp.97-104
• /
• 2015

In this paper, we propose a data envelopment analysis (DEA) and analytic hierarchy process (AHP) integrated model to improve the selection process in the acquisition of a weapon system which is the key component to the success of the project. In particular, we applied DEA in the first stage to choose a frontier group among the candidates in the selection process of the next-generation fighter system (the 3rd FX) in Korea. Then, by using the Delphi technique, we surveyed military experts and applied AHP to determine the best choice among the candidates. The results of the study match the actual decision made by the Korean government in the weapon system acquisition. The results of the proposed DEA-AHP integrated method in the selection of the next-generation fighter systems in Korea demonstrate the usefulness of the method. In this paper, we also discuss the future implications of the proposed model.

• 한국신재생에너지학회:학술대회논문집
• /
• 한국신재생에너지학회 2006년도 춘계학술대회
• /
• pp.323-324
• /
• 2006

In the present paper a forecasting system of wind power generation for Walryong Site, Jejudo is presented, which has been developed and evaluated as a first step toward establishing Korea Forecasting Model of Wind Power Generation. The forecasting model, KIER forecaster is constructed based on statistical models and is trained with wind speed data observed at Gosan Weather Station nearby Walryong Si to. Due to short period of measurements at Walryong Site for training statistical model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict technique. Three-hour advanced forecast ins shows good agreement with the measurement at Walryong site with the correlation factor 0.88 and MAE(mean absolute error) 15% under.

• KEPCO Journal on Electric Power and Energy
• /
• 제5권3호
• /
• pp.223-228
• /
• 2019

In order to integrate large amounts of variable generation resources such as wind and solar reliably into power grids, accurate renewable energy forecasting is necessary. Since renewable energy generation output is heavily influenced by environmental variables, accurate forecasting of power generation requires meteorological data at the point where the plant is located. Therefore, a spatial approach is required to predict the meteorological variables at the interesting points. In this paper, we propose the meteorological variable prediction model for enhancing renewable generation output forecasting model. The proposed model is implemented by three geostatistical techniques: Ordinary kriging, Universal kriging and Co-kriging.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2003년도 춘계학술대회 논문집
• /
• pp.1283-1287
• /
• 2003

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore. it becomes a important to handle the huge amount and various types of point data to generate a surface model efficiently. This paper proposes a new triangular mesh generation method using 3D grids. The geometric information of a part can be obtained from point cloud data by estimating normal values of the points. In our research, the non-uniform 3D grids are generated first for feature based data reduction based on the geometric information. Then, triangulation is performed with the reduced point data. The grid structure is efficiently used not only for neighbor point search that can speed up the mesh generation process but also for getting surface connectivity information to result in same topology surface with the point data. Through this integrated approach, it is possible to create surface models from scanned point data efficiently.

• 물과 미래
• /
• 제7권1호
• /
• pp.71-77
• /
• 1974

This paper reviews several different single site generation models for further development of a model for generating the Synthetic sequences of streamflow in the continuous streams like main streams in Korea. Initially the historical time series is looked using a time series technique, that is correlograms, to determine whether a lag one Markov model will satisfactorily represent the historical data. The single site models which were examined include an empirical model using the historical probability distribution of the random component, the linear autoregressive model(Markov model, or Thomas-Fiering model) using both logarithms of the data and Matala's log-normal transformation equations, and finally gamma distribution model.

• Fibers and Polymers
• /
• 제5권1호
• /
• pp.12-18
• /
• 2004

A parametric body model generation system has been developed. Using various mathematic and geometric algorithms of this system, a three-dimensionally scanned human body can be converted into a resizable body model. Once a parametric body model is formed, its size and shape can be modified instantaneously by providing appropriate anthropometric data. To facilitate the subsequent pattern arrangement process for garment drape simulation, a bounding box generation algorithm has been developed in this study. Also the model can be converted into a set of parametric surfaces that it can also be used for three-dimensional garment pattern design system.

• 한국CDE학회논문집
• /
• 제8권3호
• /
• pp.133-140
• /
• 2003

This paper describes a Multi-step Digitizing Method and Reverse Model generation algorithm for improvement of reverse engineering accuracy. Reverse engineering is the process of reproducing computational model by directly extracting geometric information on the physical objects. For the improvement of measuring data accuracy, we propose a multi-step digitizing method. First, measuring cloud-of-point by use of a laser scanning system. Second, gathering digitizing data by a scanning touch probe. Fine digitizing plan generated from coarse surface model directly from the cloud-of-point and it allows CMM more accurate scanning data. Finally in this paper we propose the algorithm of generating NURB surface from more accurate measuring points.