The Role of Rosenblatt's Perceptron in Decision-Making for Analyzing Economic Processes

This article examines the transformative role of Rosenblatt's Perceptron in econometrics and financial decision-making, emphasizing its influence on personal finance, industrial automation, and human-computer interaction. Rosenblatt's Perceptron, inspired by neural structures in the human brain, offers a dynamic learning mechanism capable of adapting to data patterns over time. In personal finance, it optimizes budgeting, savings, and expenditure management through its adaptive weight adjustments. The model's application in industrial automation enhances decision-making in resource allocation and process optimization. The article also highlights the perceptron's role in econometrics to analyze financial patterns, detect fraud, and manage risks, along with ethical considerations such as biases, data privacy, and transparency.

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