Abstract: While data-driven methods have gained prominence in wind turbine fault diagnosis, their effectiveness is increasingly constrained by the proliferation of data silos. This phenomenon ...
Abstract: In this study, the focus is to use the t-distributed Stochastic Neighbor Embedding (t-SNE) technique for identifying outliers from high dimensional data sets. To this end, the study proposes ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you’ve ever built a predictive model, worked on a ...
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