• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.363-366
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• 2001

It is very difficult to maintain the performance of estimation models for the new breed of projects since the computing environment changes so rapidly in terms of programming languages, development tools, and methodologies. So, we propose to use the relevant cases for a neural network model, whose cost is the decreased number of cases. To balance the relevance and data availability, the qualitative input factors are used as criteria of data classification. With the data sets that have the same value for certain qualitative input factors, we can eliminate the factors from the model making reduced neural network models. So we need to seek the optimally reduced neural network model among them. To find the optimally case-selective neural network, we propose the search techniques and sensitivity analysis between data points and search space.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.7 no.2
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• pp.21-26
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• 1989

This module to input Korean Level Data has 4 capacities of inputing, deleting, referencing and saving. Data file of level line consists of sorted list of node on the basis of “ABSTRACT”. For easy work, interactive method was employed. As the result of removing the boring routine by applying the characteristics of level data, working efficiency was increased. This program was written in C-language and runs on a minimum hardware configuration of IBM PC/XT with 640KB memory, In the future, these unit modules combine to form Generalized Level Information System.

• Korean Journal of Remote Sensing
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• v.3 no.2
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• pp.103-113
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• 1987

The two key elements of the Geographic Information System(GIS) are (1) Data base management of land resources information as computer files, and (2) Software ability to analyze and map this information. More geometrically corrected SPOT derived land cover information and digital topographic infornation from digitial elevation model (DEM) were integrated as input data of GIS in order to create landscape modelling. The ultimate goal of this GIS is to establish the use of physiographic data as an intergral part of the comprehensive planning process in order to avoid significant environmental and economic problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4483-4501
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• 2020

Recent findings identified the scatter and shape of MFD (macroscopic fundamental diagram) is heavily influenced by the spatial distribution of link density in a road network. This implies that the concept of MFD can be utilized to divide a heterogeneous road network with different degrees of congestion into multiple homogeneous subnetworks. Considering the actual traffic data is usually incomplete and inaccurate while most traffic partition algorithms rely on the completeness of the data, we proposed a three-step partitioned algorithm called Iso-MB (Isoperimetric algorithm - Merging - Boundary adjustment) permitting of incompletely input data in this paper. The proposed algorithm was implemented and verified in a simulated urban transportation network. The existence of well-defined MFD in each subnetwork was revealed and discussed and the selection of stop parameter in the isoperimetric algorithm was explained and dissected. The effectiveness of the approach to the missing input data was also demonstrated and elaborated.

• Journal of Environmental Science International
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• v.26 no.11
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• pp.1255-1266
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• 2017

Phosphorus (P) is an essential and major nutrient for both plants and animals. However, anthropogenic P in the environment may cause severe problems such as the deterioration of water quality. Therefore, it is essential for the Korean government to manage P in the agricultural sector. The annual P budget for Korea was 46 kg P ha-1 in 2013, placing Korea in second among Organisation for Economic Co-operation and Development (OECD) countries. P surplus and deficiency in agricultural lands can be estimated according to the P budget, which is one of the OECD agri-environment indicators. In the P budget, it is important to ensure consistency in the input-output data sources, in order to apply national and regional policies for the environmentally sound management of agricultural P. This study examines the impacts on the input-output data sources in the regional P budget in Korea. P budgets were between 99-145 kg-P/ha, depending on different data sources. We suggest two recommended data combinations (DC 1 and DC 2) for reliability of the data. P budgets calculated using DC 1 and DC 2 were 128 kg-P/ha and 97 kg-P/ha, respectively. According to the results, one of the core factors affecting P budgets was crop production. In this study, DC 2 was recommended rather than DC 1 in order to consider the cultivated areas for various crops. It is also necessary to analyze the sensitivity of the coefficients used in P budget in the future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1114-1124
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• 2015

In this paper, precipitation / non-precipitation pattern classification of meteorological radar data is conducted by using neuro-fuzzy algorithm. Structure expression of meteorological radar data information is analyzed in order to effectively classify precipitation and non-precipitation. Also diverse input variables for designing pattern classifier could be considered by exploiting the quantitative as well as qualitative characteristic of meteorological radar data information and then each characteristic of input variables is analyzed. Preferred pattern classifier can be designed by essential input variables that give a decisive effect on output performance as well as model architecture. As the proposed model architecture, neuro-fuzzy algorithm is designed by using FCM-based radial basis function neural network(RBFNN). Two parts of classifiers such as instance classifier part and echo classifier part are designed and carried out serially in the entire system architecture. In the instance classifier part, the pattern classifier identifies between precipitation and non-precipitation data. In the echo classifier part, because precipitation data information identified by the instance classifier could partially involve non-precipitation data information, echo classifier is considered to classify between them. The performance of the proposed classifier is evaluated and analyzed when compared with existing QC method.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.671-678
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• 2011

Data mining searches for interesting relationships among items in a given database. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, customer classification, etc. When create decision tree model, complicated model by standard of model creation and number of input variable is produced. Specially, there is difficulty in model creation and analysis in case of there are a lot of numbers of input variable. In this study, we study on decision tree using intervening variable. We apply to actuality data to suggest method that remove unnecessary input variable for created model and search the efficiency.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.35-44
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• 1998

In this paper, input LC filter design of diode rectifiers considering filter V A rating reduction has been propoesd. It consisted of an input LC parallel resonent tank whose inductor and capacitor values are se$.$ lected so that the input filter presents an infinite impedance to harmonic input ac current component. The operation of proposed input filter has been analyzed in detail under steady state conditions. Performance evaluation and related design data have been provided on Per Unit basis for the proper implementation of diode rectification system. Finally, Detailed input and output current analysis has shown that the proposed input filter yield high quality input ac current waveforms, in particular, high input power factor values and more reliabilty which reducing the V A rating of passive components as compared to the standard type LC filter.filter.

• Particle and aerosol research
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• v.7 no.3
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• pp.99-108
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• 2011

To establish area specific control strategies for the reduction of the ozone concentration, the Ozone Isopleth Plotting Package for Research(OZIPR) model has been widely used. However, the model results tend to changed by various input parameters such as the background concentration, emission amount of NOx and volatile organic compounds (VOCs), and meteorological condition. Thus, sensitivity analysis should be required to ensure the reliability of the result. The OZIPR modeling results for five local government districts in the Seoul Metropolitan Area (SMA) in June 2000 were used for the sensitivity analysis. The sensitivity analysis result showed that the modeling result of the SMA being VOC-limited region be still valid for a wide range of input parameters' variation. The estimated ozone concentrations were positively related with the initial VOCs concentrations while were negatively related with the initial NOx concentrations. But, the degree of the variations at each local district was different suggesting area specific characteristics being also important. Among the five local governments, Suwon was chosen to identify other variance through the period from April to September in 2000. The monthly modeling results show different ozone values, but still showing the characteristics of VOCs-limited region. Limitations due to not considering long range transport and transfer from neighbor area, limitation of input data, error between observed data and estimated data are all discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.