Literature review is an overview of existing research, it can also be used to understand research trends and directions. In recent years, the literature associated with wind power has grown rapidly, and it seems inadequate to rely on human resources to study all papers. Very few studies have used machine learning algorithms and visualization approaches to analyze the trends and directions in wind power. To explore these, we collected 50,579 articles (2012-2019) from Web of Science Core Collection (WoSCC) and 785 papers (2012-2019) from China National Knowledge Infrastructure (CNKI). We applied machine learning algorithms including text mining, word segmentation, T-Distributed Stochastic Neighbor Embedding (T-SNE), Auto-Encoder (AE), visual imagery and other methods to analyze and visually display literature in the field of wind power via analysis of the trends with time-sequence, hotspots in abstracts and keywords, and spatial distribution. China, the United States, and Iran are the top three countries in the field of wind power. Through analyzing the trends between 2012-2019, we find that research hotspots have changed. The usage rate of terms such as Power Generation Control, Power Grids, Wind Power Plants, and Wind Turbines has significantly increased, and the corresponding growth rates are 10.91%, 7.06%, 6.28% and 4.33%, respectively. This study also provides information on the relationship of words of abstracts in papers, which shows that these words are mainly divided into four categories: forecasting, optimization, investment, energy and equipment. An implication of this study is that machine learning algorithms may play an important role in the analysis of wind power literature.
In this paper, we study the uniqueness questions of finite order transcendental entire functions and their difference operators sharing a set consisting of two distinct entire functions of finite smaller order. Our results in this paper improve the corresponding results from Liu (2009) and Li (2012).
Finding exact solutions of nonlinear equations plays an important role in nonlinear science, especially in engineering and mathematical physics. In this paper, we employed the complex method to get eight exact solutions of the modified BBM equation for the first time, including two elliptic function solutions, two simply periodic solutions, and four rational function solutions. We used the exp − ϕ z -expansion methods to get fourteen forms of solutions of the modified BBM equation. We also used the sine-cosine method to obtain eight styles’ exact solutions of the modified BBM equation. Only the complex method can obtain elliptic function solutions. We believe that the complex method presented in this paper can be more effectively applied to seek solutions of other nonlinear evolution equations.
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