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🔹 Artificial neural networks mimic the brain’s functioning in a simplified way through interconnected neurons that process signals and adjust their weights to learn from data. Their layers, activation functions, and learning mechanisms help solve complex problems and recognise patterns. Their adaptability, generalisation, and parallel processing capabilities support applications in prediction, robotic control, and trajectory planning. Evolutionary optimisation can also automate the exploration
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