지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.4
- 수록면
- 262 - 269 (8page)
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초록· 키워드
오류제보하기
Productivity prediction models, which analysis regional economic potential, normally use factor analysis and factor variation measurement. In this research, a measuring model that predicts regional economic potential according to population structure was developed to chase variance of gross regional domestic product (GRDP) resulted from change of population structure. Previous models had been problems that could not consider various population structure or relationship between elements of the structure. To solve that, five-year age groups were selected as input variables and a prediction model that can consider relationship between age groups and quantitatively analysis regional productivity was developed. Artificial neural network (ANN) is a wide use model, which can consider the relationship between variables through hidden layer network and this model was applied in this research to develop the regional economic potential prediction model. Five-year age groups population and GRDP data, from 2000 to 2010, of sixteen cities and towns in Chungnam province, South Korea was used to develop regional economic potential prediction model and this model was verified with this data.
목차
ABSTRACT
I. 지역생산성 추정
II. 인구구조의 변화와 지역생산성
III. 인공신경망을 통한 지역생산성 추정
IV. 연구대상 및 범위
V. 연구결과
VI. 결론
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UCI(KEPA) : I410-ECN-0101-2014-520-003302043