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.
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초록· 키워드
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Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.
목차
1. 서론
2. 관련 알고리즘
3. 제안하는 방법론
4. 실험
5. 결론
참고문헌
참고문헌 (42)
참고문헌 신청
1. [학술지(정기간행물)] - Aggarwal, S. K / 2009 / Electricity price forecasting in deregulated markets : A review and evaluation / Electrical Power and Energy Systems 31 : 13 ~ 22
2. [학술지(정기간행물)] - Amjady, N / 2009 / Design of input vector for dayahead price forecasting of electricity markets / Expert Systems with Applications 36 : 12281 ~ 12294
3. [학술지(정기간행물)] - Amjady, N / 2008 / Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method / Electrical Power and Energy Systems 30 : 533 ~ 546
4. [학술지(정기간행물)] - Amjady, N / 2009 / Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique / Energy Conversion and Management 50 : 2976 ~ 2982
5. [학술대회논문] - Ando, R. K / 2005 / A High-Performance Semi-Supervised Learning Method for Text Chunking / Annual Meeting on Association for Computational Linguistics
2. [학술지(정기간행물)] - Amjady, N / 2009 / Design of input vector for dayahead price forecasting of electricity markets / Expert Systems with Applications 36 : 12281 ~ 12294
3. [학술지(정기간행물)] - Amjady, N / 2008 / Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method / Electrical Power and Energy Systems 30 : 533 ~ 546
4. [학술지(정기간행물)] - Amjady, N / 2009 / Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique / Energy Conversion and Management 50 : 2976 ~ 2982
5. [학술대회논문] - Ando, R. K / 2005 / A High-Performance Semi-Supervised Learning Method for Text Chunking / Annual Meeting on Association for Computational Linguistics
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UCI(KEPA) : I410-ECN-0101-2014-530-000450053