• Journal of the Korea Furniture Society
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• v.14 no.1
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• pp.35-45
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• 2003

It has shown that the investment on the new products have a direct influence on the price of manufactured goods. This brings about a point, which has been a common problem for many Korean enterprises. That is Korean products can only its international competitiveness from the price, not quality. Our industry has shown its movement from producing cheap, low quality products to creating somewhat more advanced and higher qualify products. However the industry cannot avoid the financial burden from the investment. Just like the title of this article, for existing the 3D-MODELING, the 3D-CAD is existed first has immediate effect on the many developing processes, such as planning a product, designing, and producing. The development of the furniture design in the future will be done in the same way as this article presents. This will have a great effect on the overall productivity. (Time, cost, efficiency and etc). The simulation experiment on this article is based on the idea of development of industry, forms the immediate constituent for the prediction related to the production development, marketing and the trend. Which means, this will play an important part where companies achieve satisfaction from the marketing part and the economy.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.313-317
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• 2001

The approach to predict time series without neglecting the fluctuation in a short period is tried by using a digital FIR filter and a neural network. The differential waveform of the Nikkei average closing price is filtered by the FIR band-pass filter of 101 length. It is filtered into the five frequency bands of 0-1Hz, 1-2Hz, 2-3Hz, 3-4Hz and 4-5Hz by setting the sampling frequency 10Hz. The each filtered waveform is learned and forecasted by the neural network. The neural network of the back propagation method is adopted in the learning the waveform. By inputting the data of 20 days in the past, the prediction of 10 days ahead is carried out. After learning the time series of each frequency band by the neural network, the predicted data far each frequency band are obtained. The predicted waveforms of each frequency band are synthesized to obtain a final forecast. The waveform can be forecasted well as a whole.

• Journal of Korean Society of Rural Planning
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• v.11 no.2 s.27
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• pp.1-8
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• 2005

This study is to develop a web-based integrated system for flow of agricultural products based on recent researches with engineering approach. The system stands on the basis of web for accessibility and usability. Three parts of the system consist of analysis of regional shipping characteristics using tank model, estimation of pallet load efficiency with Monte Carlo Simulation, a long term prediction of market price with reliability analysis. Besides a decision support module for selecting optimal shipping market is added through synthesizing techniques and spatial analysis using GIS and applied to Chinese cabbage of Pyeongchang in 2004.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1980-1983
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• 2005

The characteristic of sheet metal process is the few loss of material during process, the short processing time and the excellent price and strength. The sheet metal process with above characteristic is common used in industrial field, but in order to analysis irregular field problems the reliable and economical analysis method is demanded. Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behaviour. Among Finite element method, The static-implicit finite element method is applied effectively to analyze real-size auto-body panel stamping processes, which include the forming stage. In this paper, it was focussed on the drawability factors on auto-body panel stamping by AUTOFORM with using tool planing alloy to reduce law price as well as high precision from Design Optimization of ide. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.118-124
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• 2006

The characteristic of sheet metal process is the few loss of material during process, the short processing time and the excel lent price and strength. The sheet metal process with above characteristic is common used in industrial field, but in order to analysis irregular field problems the reliable and economical analysis method is demanded. Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behavior. Among Finite element method, the static-implicit finite element method is applied effectively to analyze real-size auto-body panel stamping processes, which include the forming stage. In this paper, it was focused on the drawing ability factors on auto-body panel stamping by AUTOFORM with using tool planning alloy to reduce law price as well as high precision front Design Optimization of die. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.06a
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• pp.81-85
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• 2006

The characteristic of sheet metal process is the few loss of material during process, the short processing time and the excellent price and strength. The sheet metal process with above characteristic is common used in industrial field, but in order to analysis irregular field problems the reliable and economical analysis method is demanded. Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behaviour. Among Finite element method, The static-implicit finite element method is applied effectively to analyze real-size auto-body panel stamping processes, which include the forming stage. In this paper, it was focussed on the drawability factors on auto-body panel stamping by AUTOFORM with using tool planing alloy to reduce law price as well as high precision from Design Optimization of die. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• KIEAE Journal
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• v.17 no.3
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• pp.75-81
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• 2017

Purpose: The energy consumption of apartment units is affected by the lifestyle of the residents rather than system technology. In this study the numerical analysis of assumed energy consumption correlation factors with arbitrary value due to uncertainty. It is intended to be used as a simulation correction value which can be utilized as a predicted value of actual energy usage. The correction value of the simulation is set in the developed form of the existing process that derives the actual usage amount. The simulation results used in the existing evaluation system are used to maintain the useful value as the current system evaluation scale and predict the actual capacity. Method: The method of the study is to statistically analyze the data frames of all complexes capable of collecting the annual energy usage and to reconstruct the population by adding the variables that are expected to be correlated. Repeat the data frame configuration with variables that are assumed to be highly correlated with energy use levels. Determine whether there is correlation or not. The intensity of the external characteristics of the building equipment related to the energy consumption is presented as the quantitative value. Result: The correlation between electricity consumption and trading price since 2010 is analyzed as (Correlation coefficient 0.82). These results are higher than (Correlation coefficient 0.79), which is the correlation between residential area and trading price. This paper signifies the starting point of the methodology that broadens the field of view of verification of simulation feasibility limited to the prediction technique focused on the simulation tool and the element technology scope.The diversified phenomenon reproduction method develops the existing energy simulation method.It can be completed with a simulation methodology that can infer actual energy consumption.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1410-1413
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• 2004

Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behaviour. For the finite element modeling of sheet mental forming the accurate tool model is required. Due to the geometrical complexity of real-size part stamping tools it is hard to make FE model for real-size auto-body stamping parts. In this paper, it was focussed on the drawability factors on auto-body panel stamping by AUTOFORM with using tool planning alloy to reduce law price as well as high precision from Design Optimization of die. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.3 s.234
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• pp.484-494
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• 2005

Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behaviour. For the finite element modeling of sheet mental forming the accurate tool model is required. Due to the geometrical complexity of real-size part stamping tools it is hard to make FE model for real-size auto-body stamping parts. In this paper, it was focussed on the drawability factors on auto-body panel stamping by AUTOFORM with using tool planing alloy to reduce law price as well as high precision from Design Optimization of die. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.