The 9th International Conference on Next Generation Computing 2023 (2023.12)바로가기
페이지
pp.110-113
저자
Zulfiqar Ahmad Khan, Waseem Ullah, Hikmat Yar, Noman Khan, Min Je Kim, Sung Wook Baik
언어
영어(ENG)
URL
https://www.earticle.net/Article/A448130
원문정보
초록
영어
This paper introduces a comprehensive approach to dataset standardization aimed at enhancing the effectiveness and reliability of solar power forecasting models. Leveraging multiple datasets, this study incorporates additional attributes such as atmospheric pressure and sunshine duration. These enrichments bridge critical gaps in meteorological and environmental data, facilitating more robust and precise solar power forecasting. The paper underscores the significance of these attributes, furnishes detailed equations for their computation, and presents the outcomes of their integration. It underscores their pivotal role in enabling solar energy stakeholders to make informed decisions and optimize energy production effectively.
목차
Abstract I. INTRODUCTION II. DATASET STANDARDIZATION METHOD A. Importance of atmospheric pressure and sunshine duration III. RESULTS AND DISCUSSION A. Datasets B. Evaluation Metrics C. Comparative analysis IV. CONCLUSION ACKNOWLEDGMENT REFERENCES
키워드
Solar power forecastingdataset standardizationhybrid modelsdeep learning
저자
Zulfiqar Ahmad Khan [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Waseem Ullah [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Hikmat Yar [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Noman Khan [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Min Je Kim [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Sung Wook Baik [ Intelligent Media Laboratory, Digital Contents Research Institute, Sejong University ]
Corresponding Author