While \(K\)-means clustering is used primarily for numerical measures, we often have data where the variables are categorical. A common database type that we haven’t yet met comes in the form of a ...

This paper investigates the use of a new sliding mode control for the output voltage regulation of boost converter under parametric uncertainties of load resistance and input voltage. Owing to the ...

Wind energy has been connected to the power system on a large scale with the advantage of little pollution and large reserves. While ramping events under the influence of extreme weather will cause ...

Abstract: Power grid construction projects are proceeded on the basis of the multi-department collaboration. Besides, the whole process of project management involves a huge amount of data, which is ...

SN Comput Sci. 2021; 2(3): 160. Based on the importance and potentiality of “Machine Learning” to analyze the data mentioned above, in this paper, we provide a comprehensive view on various types of ...

Abstract: The correlative change analysis of state parameters can provide powerful technical supports for safe, reliable, and high-efficient operation of the power transformers. However, the analysis ...

Informative association rule mining is fundamental for knowledge discovery from transaction data, for which brute-force search algorithms, e.g., the well-known Apriori algorithm, were developed.