For the Ningxia area, located in the arid and semi-arid regions of China, groundwater is one of the most important sources of drinking water. However, there has been little research on the application of machine learning models in predicting groundwater in this area.
Global Recognition of Literary Talents by Exceller Books aninews.in - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from aninews.in Daily Mail and Mail on Sunday newspapers.
Get latest articles and stories on Business at LatestLY. New Delhi [India], January 31: Exceller Books has introduced The International Excellence Award with the aim of acknowledging and honoring writers across diverse disciplines. These awards are bestowed upon writers in recognition of their noteworthy contributions to the realms of literature and academia. Within the Academic Reference/Textbook Writers category, accolades have been granted to four exceptional authors: Bhavya Venkatesh, the author of a children's book 'Big and Small'; Abhijit Debnath, who wrote 'Limit, Continuity & Differentiability'; Dr Vinayaka K.S, the author of Plant 'Morphology and Taxonomy', and Dr Rohit Jaysing Bhor, the writer of 'Advanced Novel Drug Medicinal Chemistry'. Business News | Global Recognition of Literary Talents by Exceller Books.
Estimating the state-of-charge (SOC) of lithium-ion batteries is essential for maintaining secure and reliable battery operation while minimizing long-term service and maintenance expenses. In this work, we present a novel Time-Series Wasserstein Generative Adversarial Network (TS-WGAN) approach for SOC estimation of lithium-ion batteries, characterized by a well-designed data preprocessing process and a distinctive WGAN-GP architecture. In the data preprocessing stage, we employ the Pearson correlation coefficient (PCC) to identify strongly associated features and apply feature scaling techniques for data normalization. Moreover, we leverage polynomial regression to expand the original features and utilize principal component analysis (PCA) to reduce the computational load and retain essential information by projecting features into a lower-dimensional subspace. Within the WGAN-GP architecture, we originally devise a Transformer as the generator and a Convolution Neural Network (CNN)