This article examines the transformative role of neural networks in econometrics and financial decision-making, emphasizing their influence on personal finance, automation, healthcare, transportation, and human-computer interaction. Neural networks, inspired by the structure of the human brain, have the potential to revolutionize these sectors by enhancing efficiency, accuracy, and decision-making capabilities. In personal finance, they can optimize budgeting, savings, and expenditure management through automated models such as the McCulloch-Pitts neuron. In healthcare, neural networks improve diagnostic capabilities and enable predictive treatment. The article also highlights the applications of neural networks in econometrics to analyze financial patterns, detect fraud, and manage risks more effectively. However, it also addresses the ethical concerns related to data privacy, security, and biases in algorithmic decision-making, stressing the importance of responsible development. Ultimately, it concludes that, despite the challenges, the benefits of integrating neural networks into econometric models and financial systems are substantial and indispensable for modern advancements.
| Mualliflar | Mirzayev, Shoxrux, Мирзаев, Шохрух, Mirzayev, Shoxrux |
|---|---|
| Jurnal | Иқтисодий тараққиёт ва таҳлил |
| Nashr sanasi | 2024-11-29 |
| Jild | 2 |
| Son | 11 |
| Betlar | 185-190 |
| Til | Ingliz |
| DOI | 10.60078/2992-877x-2024-vol2-iss11-pp185-190 |
DOI: 10.60078/2992-877x-2024-vol2-iss11-pp185-190 · Maqolaning asl sahifasi
нейронные сети, модель Маккалока-Питтса (MP нейрон), эконометрика, личные финансы, автоматизация, бинарное принятие решений, финансовое управление, бюджетирование, сбережения и траты, доходы и расходы, пороговая модель принятия решений, машинное обучение, финансовое благополучие, предиктивный анализ, структура принятия решений, neural networks, McCulloch-Pitts model (MP neuron), econometrics, personal finance, automation, binary decision-making, financial management, budgeting, savings and spending, income and expenses, threshold decision model, machine learning, financial health, predictive analysis, decision-making framework, neyron tarmoqlar, McCulloch-Pitts modeli (MP neyron), ekonometriya, shaxsiy moliya, avtomatlashtirish, ikkilik qaror qabul qilish, moliyaviy boshqaruv, byudjetlash, jamg‘arma va sarflar, daromad va xarajatlar, qaror qabul qilishning chegara modeli, mashinani o‘rganish, moliyaviy salomatlik, prediktiv tahlil, qaror qabul qilish struktura
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