• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.524-529
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• 2004

In this paper, We described the method which developed the optimal control system for air separation unit to change production rates frequently and rapidly. Control models of the process were developed from actual plant data using subspace identification method which is developed by many researchers in resent years. The model consist of a series connection of linear dynamic block and static nonlinear block (Wiener model). The model is controlled by model based predictive controller. In MPC the input is calculated by on-line optimization of a performance index based on predictions by the model, subject to possible constraints. To calculate the optimal the performance index, conditions are expressed by LMI(Linear Matrix Inequalities).In order to access at the Bailey DCS system, we applied the OPC server and developed the Client program. The OPC sever is a device which can access Bailey DCS system.The Client program is developed based on the Matlab language for easy calculation,data simulation and data logging. Using this program, we can apply the optimal input to the DCS system at real time.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.65-71
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• 2012

The objective of this study was to estimate surface runoff from rice paddy plots using an artificial neural network (ANN). A field experiment with three treatment levels was conducted in the NICS saemangum experimental field located in Iksan, Korea. The ANN model with the optimal network architectures, named Paddy1901 with 19 input nodes, 1 hidden layer with 16 neurons nodes, and 1 output node, was adopted to predict surface runoff from the plots. The model consisted of 7 parameters of precipitation, irrigation rate, ponding depth, average temperature, relative humidity, wind speed, and solar radiation on the daily basis. Daily runoff, as the target simulation value, was computed using a water balance equation. The field data collected in 2011 were used for training and validation of the model. The model was trained based on the error back propagation algorithm with sigmoid activation function. Simulation results for the independent training and testing data series showed that the model can perform well in simulating surface runoff from the study plots. The developed model has a main advantage that there is no requirement for any prior assumptions regarding the processes involved. ANN model thus can be a good tool to predict surface runoff from rice paddy fields.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.4
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• pp.242-249
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• 2004

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for the practical purpose of forecasting forest fire danger. Forest fire in South Korea is highly influenced by humidity, wind speed, and temperature. To effectively forecast forest fire occurrence, we need to develop a forest fire danger rating model using weather factors associated with forest fire. Forest fore occurrence patterns were investigated statistically to develop a forest fire danger rating index using time series weather data sets collected from 8 meteorological observation centers. The data sets were for 5 years from 1997 through 2001. Development of the forest fire occurrence probability model used a logistic regression function with forest fire occurrence data and meteorological variables. An eight-province probability model by was developed. The meteorological variables that emerged as affective to forest fire occurrence are effective humidity, wind speed, and temperature. A forest fire occurrence danger rating index of through 10 was developed as a function of daily weather index (DWI).

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.

• Structural Engineering and Mechanics
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• v.71 no.5
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• pp.469-483
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• 2019

In this paper, an improved mathematical model is presented for the bending analysis of doubly curved functionally graded material (FGM) sandwich rhombic conoids. The mathematical model includes expansion of Taylor's series up to the third degree in thickness coordinate and normal curvatures in in-plane displacement fields. The condition of zero-transverse shear strain at upper and lower surface of rhombic conoids is implemented in the present model. The newly introduced feature in the present mathematical model is the simultaneous inclusion of normal curvatures in deformation field and twist curvature in strain-displacement equations. This unique introduction permits the new 2D mathematical model to solve problems of moderately thick and deep doubly curved FGM sandwich rhombic conoids. The distinguishing feature of present shell from the other shells is that maximum transverse deflection does not occur at its center. The proposed new mathematical model is implemented in finite element code written in FORTRAN. The obtained numerical results are compared with the results available in the literature. Once validated, the current model was employed to solve numerous bending problems by varying different parameters like volume fraction indices, skew angles, boundary conditions, thickness scheme, and several geometric parameters.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.241-247
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• 2021

This study analyzed the changes in explanatory power of the modified Jones model(1995) for estimating the amount of accruals for Korean Stock Market listed companies from 1990 to 2019. We hypothesized that if the properties of financial variables used in the existing model change over time or change in discretionary ratios, the model's explanatory power will change. As the result of regression models, I found that the explanatory power of the modified Jones model(1995) gradually declined over time. The results may be derived from the increase in accruals itself and the changes in the distribution of variables contained in the model. The results of this research's chronological approach are expected to give important implications to both academic researchers and accounting information users.

• Geomechanics and Engineering
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• v.35 no.1
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• pp.13-27
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• 2023

The model production for large-scale (lateral length ≥ 2.0 m) capillary barrier (CB) model tests is time and cost-intensive. To address these limitations, the framework of a small-scale CB (SSCB) model test under the lateral no-flow condition has been established. In this study, to validate the experimental methodology of the SSCB model test, a series of seepage analyses on the SSCB model test and engineered slopes in the same and additional test conditions was performed. First, the seepage behavior and diversion length (L_D) of the CB system were investigated under three rainfall conditions. In the seepage analysis for the engineered slopes with different slope angles and sand layer thicknesses, the L_D increased with the increase in the slope angle and sand layer thickness, although the increase rate of the L_D with the sand layer thickness exhibited an upper limit. The L_D values from the seepage analysis agreed well with the results estimated from the laboratory SSCB mode test. Therefore, it can be concluded that the experimental methodology of the SSCB model test is one of the promising alternatives to efficiently evaluate the water-shielding performance of the CB system for an engineered slope.

• KIEAE Journal
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• v.1 no.2
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• pp.63-70
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• 2001

With environmental problems and pollutions accumulated by continuous towns or cities developments events, it is becoming necessary to develop in consideration of environmental effects. This consensus leads to prepare a plan system and instrument for ecological city development, which can be a series of planning indicators. To develope a series of process for environmental friendly development, this study has three main goals as follows; development of policies and programs for environmental friendly development, suggestion of environmental friendly urban design models and standards, development of planning indicators and design guidelines Korean land use plan is operated by both zoning system and detailed plan system. But the available kinds of zoning type are too limited to apply to various and vernacular places. In addition to, the detailed plan is understood to be another regulation which constricts the freedom of building right. In this study, Plan System of Environmentally Friendly Space was studied for domestic affairs In German, Plan System of Environmentally Friendly Space is the field have been progressed before. so In this study, example of German was researched intensively, and Plan System of Environmentally Friendly Space was developed, applicable for the real state in domestic. This study was focused on methodology of landscape planning and planning for afforestation. Landscape planning is performed on condition detail investigation of existent state of nature and local characteristic, and Investigation of Planning for afforestation is more detailed than that of Landscape planning. In the basis of methodology of landscape planning and planning for afforestation, Plan for Environmentally Friendly Urban Habitation Model was developed. Plan for Environmentally Friendly Urban Habitation Model was applicable for state of land use planning. Site was selected Chuk-chun in city yang-in, taking the circumstances into consideration. So landscape planning correspond to land use planning was made out. Adjustment of Land use planning and Landscape planning was very important. Undergoing this process, Plan for Environmentally Friendly Urban Habitation Model was performed.