Treffer: The Use of Neural Networks and Related Algorithms for Predictions: An Engineering Perspective.

The article focuses on the role of neural networks in modern engineering for data analysis and predictive modeling. It explains the structure of neural networks, which consist of interconnected layers of processing units, and highlights their applications in system identification, fault detection, load forecasting, predictive maintenance, and quality control. Key algorithms such as backpropagation, optimization techniques like Adam, and regularization methods are discussed, along with common architectures used in engineering, such as LSTM for predictive maintenance. The article also addresses challenges like data preprocessing and model interpretability, emphasizing the growing importance of neural networks in enhancing engineering practices. [Extracted from the article]

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