Clustering is a method of unsupervised learning, which is used in many fields as part of exploratory and statistical data analysis (Saxena et al., 2017). The main task behind clustering is to group data points into specific groups. In theory, data points belonging to the same group should ...
FWS-DL: forecasting wind speed based on deep learning algorithms 17.9 Results and discussion When it comes to quality indicators, the root-mean-square error (RMSE) is an outlier in the field of key performance indicators. However, it is a highly valuable metric to have. The mathematical expres...
A differentiable graph-theory-based mean-field term that quantifies the similarity distance between large-scale three-dimensional formations; a differentiable ellipsoid-based mean-field term that inscribes the potential energy value of dense three-dimensional obstacles. A general control framework for comp...
To overcome these limitations, this study uses robust statistics theory (Maronna et al. 2019) to estimate the appropriate dataset to be used in the training process of machine learning. 3.5.1. The Classical Robust Location Estimator The sample mean and median are considered location estimators of...
Thus, understanding risk preferences, as grounded in utility theory and applied through MPT, is crucial for effective investment decision-making that is aligned with an investor’s unique characteristics. The expected return of a portfolio can be calculated as the sum of the expected returns of ...
Field-based treatments are useful in patients with multiple contiguous lesions or widespread ultraviolet damage that could conceal subclinical lesions. Many topical agents can be used, including, but not limited to, topical 5-fluorouracil, diclofenac, or imiquimod. Photodynamic therapy combined with ...
Since they were introduced into deep learning, the CNNs have demonstrated a state-of-the-art accuracy in large-scale image classification. CNN based architectures play an important role in the processing of image data due to their unique structure in the phase of feature representation, given a...
The theory of NLMF was briefly introduced and a specific implementation was considered in order to translate the problem from the 2D to the 3D domain. The proposed methodology was initially tested on a region in Kerala, India, which was a region that was severely affected by disastrous ...