Author
Xinsong Niu
Bio: Xinsong Niu is an academic researcher from Dongbei University of Finance and Economics. The author has contributed to research in topics: Wind speed & Computer science. The author has an hindex of 7, co-authored 9 publications receiving 308 citations.
Papers
More filters
TL;DR: A forecasting system is developed based on a data pretreatment strategy, a modified multi-objective optimization algorithm, and several forecasting models that positively exceeds all contrastive models in respect to forecasting precision and stability.
189 citations
TL;DR: A developed combined model is proposed, including complete ensemble empirical mode decomposition with adaptive noise—a multi-objective grasshopper optimization algorithm based on a no-negative constraint theory—and several single models, to achieve accurate prediction results.
158 citations
TL;DR: The experimental results reveal that the proposed combined forecasting system can provide effective wind speed point and interval forecasts and is deemed more useful for the scheduling and management of electric power systems than other benchmark models.
112 citations
TL;DR: An advanced hybrid prediction system based on data reconstruction and kernel approximation (random Fourier mapping) successfully maximizes the forecasting capabilities of the component methods and effectively improves the wind speed prediction performance.
73 citations
TL;DR: In this paper, a health-related economic loss evaluation system is proposed, which deals with PM2.5 distribution, optimization of distribution parameters, and evaluation of healthrelated economic losses.
60 citations
Cited by
More filters
TL;DR: A forecasting system is developed based on a data pretreatment strategy, a modified multi-objective optimization algorithm, and several forecasting models that positively exceeds all contrastive models in respect to forecasting precision and stability.
189 citations
TL;DR: An exhaustive review and categorization of data processing in wind energy forecasting is presented, including accuracy improvement, usage frequency, consuming time, robustness to parameters, maturity, and implementation difficulty.
180 citations
TL;DR: In this article, the authors comprehensively reviewed the various deep learning technologies being used in wind power forecasting, including the stages of data processing, feature extraction, and relationship learning, and compared the forecasting performance of some popular models.
178 citations
TL;DR: The experimental results reveal that the proposed combined forecasting system can provide effective wind speed point and interval forecasts and is deemed more useful for the scheduling and management of electric power systems than other benchmark models.
112 citations
Posted Content•
TL;DR: In this paper, the authors re-examine the finance-growth nexus in China using principal components analysis and ARDL bounds testing approach to cointegration, and suggest that principal components have an effective role in examining the links between growth and financial development and, that financial development fosters economic growth.
Abstract: This article re-examines the finance-growth nexus in China using principal components analysis and ARDL bounds testing approach to cointegration. The results suggest that principal components have an effective role in examining the links between growth and financial development and, that financial development fosters economic growth.
111 citations