Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection.

The statistical analysis confirms as shown in Table 2 that all observed performance improvements are highly significant ( p < 0.001), providing strong evidence that the advantages are not due to random variation or experimental artifacts.

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However, the large effect size (d = 4.98) indicates that this difference is also practically significant, highlighting the challenge that traditional ensemble methods pose for deep learning approaches under certain extreme conditions.

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