Artificial Neural Network (original) (raw)

AI-generated Abstract

The paper discusses artificial neural networks (ANNs), focusing on their structure and functionality compared to traditional computational methods. It highlights their applicability in situations where algorithmic solutions are not feasible and emphasizes their role in extracting meaningful patterns from extensive datasets. The text provides a detailed overview of the feedforward network architecture, output calculations, and the process of weight adjustments within neural networks, illustrating their versatility across various domains, including aerospace, automotive, and banking.

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