A proposed hybrid model of ANN and KNN for solar cell defects detection and temperature prediction using fuzzy image segmentation.

This paper presents a novel hybrid model employing Artificial Neural Networks (ANN) and Mathematical Morphology (MM) for the effective detection of defects in solar cells. Focusing on issues such as broken corners and black edges caused by environmental factors like broken glass cover, dust, and temperature variations. This study utilizes a hybrid model of ANN and K-Nearest Neighbor (KNN) for temperature prediction.

A proposed novel adaptive DC technique for non-stationary data removal.

The stationarity of a time series is an important assumption in the Box-Jenkins methodology. Removing the non-stationary feature from the time series can be done using a differencing technique or a logarithmic transformation approach, but it is not guaranteed from the first step. This paper proposes a new adaptive DC technique, a novel technique for removing a non-stationary time series from the first step.