Wind Speed Forecasting System Based on the Variational Mode Decomposition Strategy and Immune Selection Multi-Objective Dragonfly Optimization Algorithm

التفاصيل البيبلوغرافية
العنوان: Wind Speed Forecasting System Based on the Variational Mode Decomposition Strategy and Immune Selection Multi-Objective Dragonfly Optimization Algorithm
المؤلفون: He Bo, Xinsong Niu, Jianzhou Wang
المصدر: IEEE Access, Vol 7, Pp 178063-178081 (2019)
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE), 2019.
سنة النشر: 2019
مصطلحات موضوعية: Scheme (programming language), Artificial intelligence, Mathematical optimization, General Computer Science, Computer science, 020209 energy, combined forecasting system, 02 engineering and technology, Wind speed, data preprocessing, 0202 electrical engineering, electronic engineering, information engineering, wind speed forecasting, General Materials Science, Physics::Atmospheric and Oceanic Physics, computer.programming_language, Wind power, business.industry, General Engineering, developed optimization algorithm, Nonlinear system, 020201 artificial intelligence & image processing, lcsh:Electrical engineering. Electronics. Nuclear engineering, Data pre-processing, business, lcsh:TK1-9971, computer
الوصف: In the development of the wind power industry, short-term wind speed forecasting is necessary, and many researchers have made substantial efforts to establish wind speed prediction models. However, realizing the accurate prediction of wind speeds remains a challenging task. The current prediction models do not consider the preprocessing of the data, and each model has various shortcomings. Considering the disadvantages of the available models, in this paper, an advanced combined forecasting system is applied that utilizes a data preprocessing strategy and parameter optimization strategy to obtain accurate prediction values. The proposed prediction system employs linear and nonlinear models that can take into account the characteristics of wind speed sequences, successfully combine the advantages of various single models, and yield accurate and stable prediction values. Finally, according to the experimental analysis and discussion, the proposed combined prediction system outperforms the compared models in prediction. In conclusion, the powerful combined prediction model provides a feasible scheme for wind power prediction.
تدمد: 2169-3536
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb52fbd831a8722db80de9ccbb021a8aTest
https://doi.org/10.1109/access.2019.2957062Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....fb52fbd831a8722db80de9ccbb021a8a
قاعدة البيانات: OpenAIRE