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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.
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 &a...
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 techni...
An engineer with 12 years’ experience who is also a YouTuber explains in detail why Samsung’s moon shots are the real deal
In recent years, in order to achieve the goal of 'carbon peaking and carbon neutralization', many countries have focused on the development of clean energy, and the prediction of photovoltaic power generation has become a hot research topic. However, many traditional methods only use meteorological factors such as temperature and irradiance as the features of photovoltaic power generation, and they rarely consider the multi-features fusion methods for power prediction. This paper first preprocesses abnormal data points and missing values in the data from 18 power stations in Northwes...