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장경원(Jang, Kyung Won),김종순(Kim, Jong Soon) 서울행정학회 2012 한국사회와 행정연구 Vol.23 No.3
This study categorized research on public expenditure from the last 10 years and analyzed the main trends through a meta-analysis. Themes in government expenditure, drawn form public finance textbooks and journals, are divided into three groups: overall expansion of public finance, public service demand, and public service costs. The findings are as follows. First, studies on the overall expansion of public finance examined theories of expansion and determinants of the budget structure. Empirical studies in this area supported Wagner’s Law for the most part, and confirmed that government expenditure is related to budgetary incrementalism, socioeconomic variables, and bureaucratic behavior in support of the local community. Second, studies about public service demand discussed the measurement of demands, the characteristics of public services, and intergovernmental grants. A direct measure of the demand of public goods is expected to be developed in the future. Studies on the publicness of public services and intergovernmental grants report different results than studies based upon traditional theory. Third, studies on public service costs can be classified into studies on economies of scale, factor prices, the Tiebout hypothesis, and environmental factors. These studies proved the benefits of economies of scale and confirmed that city-county consolidation can hinder efficiency. On the other hand, studies about factor prices are in their infancy and there are limits to the application of the Tiebout hypothesis in the Korean context, due to the lack of variety in local government structures. Finally, environmental factors were found to have a noticeable effect on government expenditure, and demographic factors in particular.
퍼지 결합 다항식 뉴럴 네트워크 기반 패턴 분류기 설계
노석범(Seok-Beom Rho),장경원(Kyung-Won Jang),안태천(Tae-Chon Ahn) 대한전기학회 2014 전기학회논문지 Vol.63 No.4
In this paper, we propose a fuzzy combined Polynomial Neural Network(PNN) for pattern classification. The fuzzy combined PNN comes from the generic TSK fuzzy model with several linear polynomial as the consequent part and is the expanded version of the fuzzy model. The proposed pattern classifier has the polynomial neural networks as the consequent part, instead of the general linear polynomial. PNNs are implemented by stacking the simple polynomials dynamically. To implement one layer of PNNs, the various types of simple polynomials are used so that PNNs have flexibility and versatility. Although the structural complexity of the implemented PNNs is high, the PNNs become a high order-multi input polynomial finally. To estimate the coefficients of a polynomial neuron, The weighted linear discriminant analysis. The output of fuzzy rule system with PNNs as the consequent part is the linear combination of the output of several PNNs. To evaluate the classification ability of the proposed pattern classifier, we make some experiments with several machine learning data sets.
A Note on Intuitionistic Fuzzy Subgroups
Tae-Chon Ahn(안태천),Kyung-Won Jang(장경원),Seok-Beom Roh(노석범),Kul Hur(허걸) 한국지능시스템학회 2005 한국지능시스템학회 학술발표 논문집 Vol.15 No.2
In this paper, We discuss various types of sublattice of the lattice of intuitionistic fuzzy subgroups of a given group. We prove that a special class of intuitionistic fuzzy normal subgroups constitutes a modular sub lattice of the lattice of intuitionistic fuzzy subgroups. Moreover, we exhibit the relationship of the sublattices of the lattice of intuitionistic fuzzy subgroups.