• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.139-148
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• 2010

This paper shows a reinforcement post-processing method and feedback algorithm for improvement of assigning method in classification. Especially, we focused on complex documents that are generally considered to be hard to classify. A basis factors in traditional classification system are training methodology, classification models and features of documents. The classification problem of the documents containing shared features and multiple meanings, should be deeply mined or analyzed than general formatted data. To address the problems of these document, we proposed a method to expand classification scheme using decision boundary detected automatically in our previous studies. The assigning method that a document simply decides to the top ranked category, is a main factor that we focus on. In this paper, we propose a post-processing method and feedback algorithm to analyze the relevance of ranked list. In experiments, we applied our post-processing method and one time feedback algorithm to complex documents. The experimental results show that our system does not need to change the classification algorithm itself to improve the accuracy and flexibility.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.95-102
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• 2010

As the electric power industry is evolving into competitive market scheme, a new paradigm is required for the operation of market. Traditional dispatch algorithm was built based on the optimization model with an objective function and multiple constraints. Commercial market simulator followed the concept of the microeconomic model used in the dispatch algorithm, which is called as analytic method. On analytic method it is prerequisite to procure the exact data for the simulation. It is not easy anymore for each market participant to access to other participants' financial information while it used to be easy for monopoly decision maker to know all the information needed for the optimal operation. Considering the changing situation, it is required to introduce a new method for estimating the market price. This paper proposes an empirical method based on stochastic processes expected to build a capacity planning and long term contracts.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.212-217
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• 2009

There are rule-based learning method and statistic based learning method and so on which represent learning method for hierarchy relation between domain term. In this paper, we propose to leveling and similarity measure using the extended AHP of fuzzy term in Information system. In the proposed method, we extract fuzzy term in document and categorize ontology structure about it and level priority of fuzzy term using the extended AHP for specificity of fuzzy term. the extended AHP integrates multiple decision-maker for weighted value and relative importance of fuzzy term. and compute semantic similarity of fuzzy term using min operation of fuzzy set, dice's coefficient and Min+dice's coefficient method. and determine final alternative fuzzy term. after that compare with three similarity measure. we can see the fact that the proposed method is more definite than classification performance of the conventional methods and will apply in Natural language processing field.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.517-526
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• 2014

This paper performed studies on a guide for an environmental assessment necessary to select railroad route optimally, and presented techniques for an environmental friendly route selection using AHP(Analytical Hierarchy Process) as an objective method. The AHP is an approach to decision making that involves multiple choice criteria into a hierarchy and assessing the relative importance of each criterion, and determining an overall ranking of the alternatives. For the purpose of this study, we established the weight and the order of major environmental assessment items based on the survey of experts. The results of the weight by AHP were in order of Fauna & Flora, Topography & Geology, Nature Environmental Assets, Noise & Vibration, Water Quality, Landscape and Air Quality indicating natural environment should be in priority. To develop the more efficient environmental friendly route selection systems, it is necessary to consider economical, technical, and social aspects in addition to environmental consideration.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.1-21
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• 2003

As electronic commerce(EC) has grown rapidly, agents that work on the behalf of humans on the Internet are being used actively. However, most of the EC agents have some problems. They fail to fully support buyers' decision making behaviors and sellers' information supply activities. Further, they are not suited for mobile computing environment. In this paper, we introduce a Multi-Mobile Agents System(MMAS) that has been developed according to a conceptual framework that corrects the aforementioned problems. Built by using Tokyo IBM ASDK(Aglets Software Development Kit) for the area of hotel reservation, the system consists of buyer- and seller-side agents that interact with each other; buyer-side agents help buyers to make purchasing decisions by collecting and analyzing information through applying a multi-criteria decision making method, while seller-side agents substitute fur sellers by managing databases and providing real-time information to the buyer-side agents. In this system, multiple agents perform their shared tasks at the same time in order to increase efficiency. Users do not have to keep the connection with the system because they are notified when tasks are done.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1921-1929
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• 2015

The smart substation is the heart of a transmission system, which is particularly emphasized as the most significant composition of smart grids in China. In order to assess the functionality performance of substation technologies, this paper presents methods used to identify the most promising solutions for smart substation design and to evaluate the technical levels of available technologies. The multi-index optimization model is presented to address the issue of smart substation planning. A mathematical model of the planning decision problem is established with multiple objectives consisting of economic, reliability, and green key indices, and many kinds of concerns including physical and environmentally friendly operations are formulated as a set of constraints. With respect to the assessment of the technical level regarding integration of advanced technologies into a substation, a modified grey whitenization weight function is adopted to structure a novel grey clustering method. The proposed grey clustering approach is used to overcome the difficulty of insufficient quantitative assessment capacity for traditional methods. The evaluation of technical effects provides the classification definition for the development phase and the maturity level of the smart substation. The effectiveness of the proposed approaches in planning decision-making and evaluation of construction efforts is demonstrated with case studies involving the actual smart substation projects of Wenchongkou substation in China Southern Power Grid (CSG) and Mengzi substation in State Grid Corporation of China (SGCC).

• Health Policy and Management
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• v.9 no.1
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• pp.110-138
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• 1999

This study intended to understand the factors influencing the utilization of charged retirement home services for the elderly by stage of discision making. At the same time the purpose of the study is also to present the results of this study as data for the expectation of the demand. The subject of this study was non-utilizer (635 persons) and utilizer (62 persons) of charged retirement home services over the age of sixty. Non-utilizer was selected by random sampling in urban and rural area, and utilizer was investigated by census survey in the three charged retirement home. The research method was interview survey by questionaire. The questionaire was composed of 59 items, 25 variables, 5 components. The research model was to add Andersen's Prediction Model. The components were predisposing component, enabling component, need component, actualizing component, psychologic component. The results of this study were as follows. 1)In the stage of recognizing the residence problem, the recognizer were 76.7% (487 persons) of all the non-utilizer. The factors of influencing were property (B=-4.1E-05), solidarity with children (B=-.1070), house satisfaction (B=-.2517), need of charged retirement home (B=.2614). 2)In the stage of selecting an altenative as utilizing of charged retirement home services, the selecter were 41.1% (261 persons) of all the non-utilizer. The factors of influencing were perception of charged retirement home (B=.2790), need of charged retirement home (B=.2971). 3)In the stage of decion-making, the decider were 29.6% (188 persons) of all the non-utilizer. The factor of influencing was need of charged retirement home (B=.3570). 4)In the stage of the actualization, the factors of influencing were charge ability of utilization (B=.1025), significant others (B=.1868). The upper results were implemented by using the statistical methods of frequency, t-test, $$\chi$^{2}$-test, multiple logistic regression ( and P 〈 .05 ).

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.25-32
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• 2013

Due to increasing competition of globalization and fast technological improvements the appropriate method for evaluating and selecting IS-personnel is one of the key factors for an organization's success. Personnel selection is a multi-criteria decision-making (MCDM) problem which consists of both qualitative and quantitative metrics. Although many articles have discussed various knowledge and skills IS personnel should possess, no specific model for IS personnel selection and evaluation, to our knowledge, has been published up to now. After reviewing the IS personnel's important characteristics, we propose an approach for categorizing the IS personnel based on their skills, ability, and knowledge during evaluation and selection process. Our proposed approach is derived from a model of neural network algorithm. We have adapted and implemented the fuzzy ART algorithm with Jaccard choice function. The result of an illustrative numerical example is proposed to demonstrate the easiness and effectiveness of our approach.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.84-90
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• 2010

In this paper, we propose a quadratic discriminant analysis based approach for improving the discriminating strength of weak classifiers based on simple Haar-like features that were used in the Viola-Jones object detection framework. Viola and Jones built a strong classifier using a boosted ensemble of weak classifiers. However, their single threshold (or decision boundary) based weak classifier is sub-optimal and too weak for efficient discrimination between object class and background. A quadratic discriminant analysis based approach is presented which leads to hyper-quadric boundary between the object class and background class, thus realizing multiple thresholds based weak classifiers. Experiments carried out for car detection using 1000 positive and 3000 negative images for training, and 500 positive and 500 negative images for testing show that our method yields higher classification performance with fewer classifiers than single threshold based weak classifiers.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.