• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.373-376
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• 2018

Traditional paprika smart farm systems are often harmful to paprika growth because they are set to follow the values of several sensors to the reference value, so the system is often unable to make optimal judgement. Using decision tree techniques, the expert system for the paprika smart farm is designed to create a control system with a decision-making structure similar to that of farmers using data generated by factors that depend on their surroundings. With the current smart farm control system, it is essential for farmers to intervene in the surrounding environment because it is designed to follow sensor values to the reference values set by the farmer. To solve this problem even slightly, it is going to obtain environmental data and design controllers that apply decision tree method. The expert system is established for complex control by selecting the most influential environmental factors before controlling the paprika smart farm equipment, including criteria for selecting decisions by farmers. The study predicts that each environmental element will be a standard when creating smart farms for professionals because of the interrelationships of data, and more surrounding environmental factors affecting growth.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.45-54
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• 1997

A mathodology to manage effectively urban open space using GIS(Geographic Information System) was developed to explore the methology of efficient urban open space management focusing on landscaped trees. Cartographic modeling technique was used for practical use of GIS as a case study of the Childeren's park in Kwangju city. First, spatial and attribute information for efficient landscaped tree management was acqired through the development of a tree management cartographic model. Second the information of location and the attribute of individual trees can be applied as a means of decision making in tree management. Thira optimal path of tree management and priority of management in work process of the selected urban open space could be determined according to the objective of park management.

• Journal of Service Research and Studies
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• v.2 no.2
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• pp.35-43
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• 2012

Data mining is an interest area in all field around us not in any specific areas, which could be used applications in a number of areas heavily. In other words, it is used in the decision-making process, data and correlation analysis in hidden relations, for finding the actionable information and prediction. But some of the data sets contains many missing values in the variables and do not exist a large number of records in the data set. In this paper, missing values are handled in accordance with the model tree algorithm. Cholesterol value is applied for predicting. For the performance analysis, experiments are approached for each treatment. Through this, efficient alternative is presented to apply the missing data.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• Journal of Forest and Environmental Science
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• v.32 no.3
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• pp.291-301
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• 2016

One of the most concerned topics in ecology is the relationship between biodiversity and ecosystem functioning. However, there are few field studies, carried out in forests, although many studies have been done in controlled experiments in grasslands. In this paper, we describe the relationship pattern between three facets of diversity and productivity at Ratargul Fresh Water Swamp Forest (RFWSF) in Bangladesh, which is the only remaining fresh water swamp forest of the country. Sixty sample plots were selected from RFWSF and included six functional traits including leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), tree height, bark thickness and wood density. In analyzing TD, we used Shannon diversity and richness indices, functional diversity was measured by Rao's quadratic entropy (Rao 1982) and Faith's (1992) index was used for phylogenetic diversity (PD). It was found that, TD, FD and PD were positively related with productivity (basal area) due to resource use complementarity but surprisingly the best predictor of tree productivity was FD. The results contribute to the understanding the effects of biodiversity loss and it is essential for conservation decision-making and policy-making of Ratargul Fresh Water Swamp Forest.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.1-22
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• 1997

This paper was focused on the efficient management of landscape woody plants, and concerned itself with their important role in the urban environment. Based on the philosophy that there is nothing that can be done without an inventory, the purpose of this study was to develop an inventory system and iris proper application to a site for establishing a management plan Two different approaches were used, The first was to make a newly structured inventory system through collecting, analyzing, and evaluating various types of inventories used in Korea, the U. S. A., and Japan. The second approach was to apply a newly designed inventory system to the case study area. using GIS 'as a tool of spacial analysis and statistics for making decisions. The results could be summarized as follows; 1. In Korea, most of the Landscape Woozy Plants Inventories had datas which represented possession of trees, and only the work which they had done according to their traditional ways, There was no data related to the conditions, management needs, and site conditions of individual trees, This is essential information for organizing an inventory system . 2. There needs to be data which is balanced, containing tree characteristics and site characteristics. Through such information the management needs could be adjusted properly. The inventory list described in this paper was determined by botanical identity, placement condition, condition of tree, and types of work for maintaining as well as improving the condition of each tree One of the most important things was to determine the location data of each tree so as to compare data with other trees. The data gained from the field survey still had some problems because of lack of scientific method for supporting objective views, and because of actual situations, especially in the field of evaluating site conditions and management needs. All data should be revised to fit a computer data management system , if possible 3. The GIS(Geographic Information System) application showed good performance in handling inventory data for decision making. All the data used for the GIS application was divided into location and non-spatial data. Using the location data, it was easy to find the exact location of each tree on the monitor and on the maps generated by the computer even in the actual managed trite, along with various attribute data. Therefore it could be said that the entire management plan should start from data of individual trees with their exact locations, for making concrete management goals through actual budget planning.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.221-233
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• 2013

This study aims to develop the severity-adjusted length of stay(LOS) model for acute stroke patients using data from the hospital discharge survey and propose management of length of stay(LOS) for acute stroke patients and using for Hospital management. The dataset was taken from 23,134 database of the hospital discharge survey from 2004 to 2009. The severity-adjusted LOS model for the acute stroke patients was developed by data mining analysis. From decision making tree model, the main reasons for LOS of acute stroke patients were acute stroke type. The difference between severity-adjusted LOS from the decision making tree model and real LOS was compared and it was confirmed that insurance type and bed number of hospital, location of hospital were statistically associated with LOS. And to conclude, hospitals should manage the LOS of acute stroke patients applying it into the medical information system.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Journal of Korea Technology Innovation Society
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• v.6 no.3
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• pp.373-390
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• 2003

With limited resources, proper allocation of the national R&D budget is very crucial matter for reinforcing the national competence, and the importance of selecting strategic R&D fields have been increasingly emphasized by technology policy-makers and CTOs. This paper deals with technology relevance/cluster analysis, which measures technological dependency and relevancy among technologies, and how it can be used for selecting the strategic R&D fields especially satisfying SMEs(small and medium enterprises)' specific needs. As a result of this study, technology-product tree composed of 7 major technology fields, 22 clusters, 41 groups, 335 core-need technologies and hundreds of related business items are produced that can be used for designing SMEs' R&D/business portfolio as well as R&D investment decision-making of the Ministry of Small and Medium Business Administration.