THE ECONOMIC SIGNIFICANCE OF ADALINE NEURAL NETWORKS IN FINANCIAL DECISION -MAKING
Abstract
This article explores the application of the ADALINE (Adaptive Linear Neuron) model in personal finance, emphasizing its role in improving decision -making accuracy. ADALINE, introduced by Bernard Widrow and Ted Hoff in 1960, utilizes gradient descent to it eratively adjust weights, enabling it to adapt to financial patterns dynamically. The study demonstrates how ADALINE enhances financial management by optimizing budgeting, saving, and expenditure decisions. Experimental results confirm that ADALINE minimiz es prediction errors over time, making it a valuable tool for managing complex financial systems. Despite its reliance on linear relationships, ADALINE proves to be a powerful approach for adaptive financial decision -making.
Keywords
ADALINE, neural networks, personal finance, adaptive learning, financial decision -making, gradient descent, budgeting, saving, expenditure management
References
- McCulloch, W. S., & Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Biophysics, 5(4), 115 -133.
- Widrow, B., & Hoff, M. E. (1960). Adaptive switching circuits. 1960 IRE WESCON Convention Record, Part 4, 96 -104.
- Widrow, B. (1962). Generalization and information storage in networks of ADALINE neurons. Self-Organizing Systems, 435 -461.
- Rakhimov, A. N., Makhmatkulov, G. K., & Rakhimov, A. M. (2021). Construction of econometric models of development of services for the population in the region and forecasting them. The American Journal of Applied Sciences, 3(02), 21 -
- Mukhitdinov, K. S., & Rakhimov, A. M. Providing accommodation and food services to the population of the region. International Journal of Trend in Scientific