• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.9 no.1
• /
• pp.102-110
• /
• 2000

This paper presents an algorithm of local map building for autonomous robot navigation using LASER range finder information. We develop a model of sensor output for a LASER range finder, and obtain an output data of the LASER range finder for a given environment. From the output data, a local map is obtained through the following procedures: (1) filtering of output data to remove noisy and unnecessary data, (2) comparison of filtered data with the original data to restore useful data, (3) thickening of the map obtained from the restored data, and (4) skeletonizing of the thickened map to get a final local map. Through some simulation studies, a map is obtained from the LASER range finder information for a given indoor environment, and is compared with the environment.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.273-275
• /
• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Journal of Integrative Natural Science
• /
• v.13 no.4
• /
• pp.147-151
• /
• 2020

In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

• Journal of Information Technology Applications and Management
• /
• v.21 no.4_spc
• /
• pp.381-401
• /
• 2014

This study proposes the accurate economic effect (employment inducement coefficient, hiring inducement coefficient, index of the sensitivity of dispersion, index of the power of dispersion, and ratio of value added) of Korea software industry by analyzing the inter-industry relation using the modified inter-industry table. Some previous studies related to the inter-industry analysis were reviewed and the key problems were identified. First, in the current inter-industry table publishedby the Bank of Korea, the output of software industry includes not only the output of pure software industry (package software and IT services) but also the output of non-software industry due to the misclassification of the industry. This causes the output to become bigger than the actual output of the software industry. Second, during rewriting the inter-industry table, the output is changing. The inter-industry table is the table in the form of rows and columns, which records the transactions of goods and services among industries which are required to continue the activities of each industry. Accordingly, if only an output of a specific industry is changed, the reliability of the table would be degraded because the table is prepared based on the relations with other industries. This possibly causes the economic effect coefficient to degrade reliability, over or under estimated. This study tries to correct these problems to get the more accurate economic effect of the software industry. First, to get the output of the pure software section only, the data from the Korea Electronics Association(KEA) was used in the inter-industry table. Second, to prevent the difference in the outputs during rewriting the inter-industry table, the difference between the output in the current inter-industry table and the output from KEA data was identified and then it was defined as the non-software section output for the analysis. The following results were obtained: The pure software section's economic effect coefficient was lower than the coefficient of non-software section. It comes from differenceof data to Bank of Korea and KEA. This study hasa signification from accurate economic effect of Korea software industry.

• Proceedings of the Technology Innovation Conference
• /
• 1997.07a
• /
• pp.160-171
• /
• 1997

This paper starts out by reviewing the literature that in different ways utilizes patent data as a output of R&D investment. The main focus, however, is an analysis of time-lag between R&D input and output. To achieve this research objective, the basic data associated with the R&D input(expenditure, researchers) and output(patent, utilities) for the past 15 years, from 1980 to 1994, in the areas of electrical-electronic, mechanical and chemical industries have been collected. And the raw output data were altered it to objective data using Laspeyres approach and analyzed using multiple regression analysis, especially stepwise regression analysis. The result of this study can be summarized as follows: a) The time-lag between R&D input and output is from 1 to 4 years. This result is equal to the research conclusion of the existing foreign studies. b) It was found that the time-lag of patents was longer than of utility models. c) It was showed that the time-lag of electrical-electronic, mechanical industry was longer than the chemical one.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.2
• /
• pp.65-73
• /
• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• The Journal of Fisheries Business Administration
• /
• v.42 no.1
• /
• pp.85-96
• /
• 2011

We have done the input-output analysis to see the over all impact of flounder industry of Jeju region on the domestic economy of Korea. To do the input-output analysis, we have constructed the data set for the input-output table by using the existing data set in the "2003 input- output table of Jeju regional area" published by the joint work of Jeju branch of Korea bank and the Jeju Development Institute, together with some raw data provided by Jejudo Marine Fish-Culture Cooperative. We have also produced input coefficient of flounder industry by making flounder industrial sector exogenous, separated from intermediate demand. To summarize our empirical results, the inducement effect of production, value added, and employment of Jeju flounder aquaculture industry are 300 billion won, 116 billion won and 1,800 people respectively. In conclusion, the results of this study suggest flounder industry of Jeju region contributes powerfully to not only Jeju economy but also all over the Korea economy.

• Current Photovoltaic Research
• /
• v.7 no.3
• /
• pp.71-75
• /
• 2019

Solar energy is one of the renewable energy sources. It can respond to expanding energy demand. A solar cell module is designed to have a durability that can be developed over a long period of 25 years to be installed outdoors and perform like a stable power supply. We need Standard Test Condition (STC)-based power output data before and after testing to measure the power output of existing modules. The modules are shown to reduce power output by comparing data before and after outdoor experiments regardless of whether they are indoor or outdoor. It is easy to compare the power output quantities through the module simulator in the indoor. However, it takes a lot of testing time and costs to compare the power output on outdoor in the case of a high number of modules and distance from the module simulator. It can save time and costs if we can check the power output using the data in outdoor. We have used the long-term outdoor test to find the elements out that corresponds to the reductions in power output quantities. We have conducted research that matched the actual and the tests.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.58 no.4
• /
• pp.602-608
• /
• 2009

In this thesis, output voltage, current and power of solar module were classified by irradiation from data of overall operating characteristics collected for one year in order to manage efficient photovoltaic generation system and deliver maximum power. In addition, from these data, correlations between irradiation of photovoltaic cell and amount of power given by photovoltaic cell was quantitatively examined to deduce optimization of the design and construction of photovoltaic generation system. As I-V characteristics according to a temperature range of 10~50[$^{\circ}C$], the area of I-V characteristics were increased with an increase in temperature. Since this area corresponds to the power, output power is thought to have increased with temperature. As output power characteristics according to a temperature range of 10~50[$^{\circ}C$], output power was increased with an increase in temperature. Since output power increases with temperature increase, the result corresponds well to the related equation on temperature and output power. As I-V characteristics according to a irradiation range of 100~900 [$W/m^2$], voltage and current were increased with an increase in irradiation. The result is thought of as an increase in output power with increasing irradiation. As output power characteristics according to a irradiation range of 100~900 [$W/m^2$], output power was increased with increasing irradiation. This result corresponds well to the related equation on irradiation and output power.

• KEPCO Journal on Electric Power and Energy
• /
• v.8 no.2
• /
• pp.55-59
• /
• 2022

This paper introduce Renewable Energy forecasting technology, which is a part of renewable management system. Then, calculation method of dedicated transmission line's meteorological data to forecast renewable energy is suggested. As the case of dedicated transmission line, there is only power output data combined the number of renewable plants' output that acquired from circuit breakers. So it is need to calculate meteorological data for dedicated transmission line that matched combined power output data. this paper suggests two calculation method. First method is select the plant has the largest capacity, and use it's meteorological data as line meteorological data. Second method is average with weight that given according to plants' capacity. In case study, suggested methods are applied to real data. Then use calculated data to Renewable forecasting and analyze the forecasting results.