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김욱동 세계문학비교학회 2002 世界文學比較硏究 Vol.6 No.-
This article aims at investigating in detail the origin and development of American national literature. It focuses on how material growth fostered cultural expansion, creating a climate in which writers could forge a new literature---a literature typically American in theme and setting and often characterized by the nation's mood of youthful optimism. Although cries for literary nationalism in America were strong enough before the Revolutionary War, it was only after the American colony was politically emancipated from the rule of the British Crown that a national literature in the proper sense of the word began to emerge. Never totally free of European and English influences, the Hartford Wits, like Timothy Dwight, John Trumbull, Joel Barlow, Lemuel Hopkins, David Humphreys, and Elihu Hubbard Smith, attempted in their own ways to pave the way for establishing a national literature in America. Philip Freneau in poetry and James Fenimore Cooper in his "Leatherstocking Tales" developed American literary nationalism one step further. It might be argued, however, that national literature in America was completed in significant ways by Walt Whitman and Mark Twain. In his Leaves of Grass, Whitman created what might be called truly American literature not only in subject matter and themes but in forms and techniques as well. On the other hand, Twain in his novels emancipated American literature from the tyranny of its British counterpart, creating a new literature uniquely American in themes and techniques.
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상관관계 분석을 통해 선택된 입력변수를 이용한 단일 입력 기반 퍼지 모델 설계
김욱동,오성권 한국지능시스템학회 2019 한국지능시스템학회논문지 Vol.29 No.6
In this paper, a new methodology to select the input variables is introduced through analyzing the correlation between input and output and also the design methodology of a single variable-based TSK fuzzy model is presented by using the selected input variables. In order to deal with high-dimensional problems, selecting essential input variables serves as an important role in improving the structure as well as the learning efficiency of a model by eliminating unnecessary variables. Therefore, the correlation coefficients between individual inputs and output are obtained, and then some of which has a large linear relationship between input and output are selected in this study. In a high dimensional problem, the conventional fuzzy inference system not only requires a long computing time but also suffers an over-fitting problem due to exponential increase of fuzzy rules. To solve such problem, a single variable-based TSK fuzzy model is constructed independently by using the selected input variables by means of correlation analysis, and as a result, the increase of fuzzy rules is minimized and an interpretability of each TSK fuzzy model is enhanced. 본 논문에서는 입-출력사이의 상관관계를 분석을 통해 입력변수를 선택하는 방법을 소개하며 선택된 입력변수를 이용하여단일 변수기반 퍼지 모델의 설계방법론이 제시된다. 고차원 문제를 다루는데 있어 중요한 입력변수 선택은 불필요한변수를 제거함으로써 모델 구조 및 학습의 효율을 높이고 성능을 개선하는데 중요한 역할을 한다. 따라서 본 연구에는각각의 입-출력사이의 상관계수를 구하여 입-출력사이의 선형관계가 큰 입력변수들을 선택한다. 고차원 문제에서 기존퍼지 추론 시스템은 입력변수에 비례한 지수적인 퍼지 규칙 생성으로 인해 많은 연산시간이 필요할 뿐만 아니라 과적합문제에 직면하게 된다. 이를 해결하기 위해 상관계수 분석을 통해 선택된 입력변수마다 독립적인 단일 변수기반 퍼지 모델을생성하여 규칙 생성을 최소화하며 각 모델의 해석력을 높인다
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