This article covers stages such as determining nonlinear trends of time series, mathematical modeling, finding trend equations using regression methods, and forecasting. In particular, taking into account the complex dynamics of economic processes, the advantages of exponential, logarithmic, and polynomial models were analyzed. The accuracy and error criteria of the forecast results are considered using practical examples.
| Mualliflar | Raximov , Nuriddin, Qutbiddin , A’zamzoda, Bozorov , Asqar, Murodov, Sardor, Рахимов , Нуриддин, Кутбиддин, Аъзамзода, Бозоров , Аскар, Муродов , Сардор, Raximov , Nuriddin, Qutbiddin , A’zamzoda, Bozorov , Asqar, Murodov , Sardor |
|---|---|
| Jurnal | Иқтисодий тараққиёт ва таҳлил |
| Nashr sanasi | 2025-06-30 |
| Jild | 3 |
| Son | 6 |
| Betlar | 253-258 |
| Til | O‘zbek |
| DOI | 10.60078/2992-877x-2025-vol3-iss6-pp253-258 |
DOI: 10.60078/2992-877x-2025-vol3-iss6-pp253-258 · Maqolaning asl sahifasi
time series, economic processes, trend, mathematical modeling, regression, временные ряды, экономические процессы, тренд, математическое моделирование, регрессия, vaqtli qatorlar, iqtisodiy jarayonlar, trend, matematik modellash, regressiya
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