An overview: Modeling and forecasting of time series data using different techniques in reference to human stress

Abstract

Forex is an important currency indicator. The index is a major factor in the development of the country. This look examines the effects of currency trading on the Random stroll version, Exponential Smoothing One, Double Exponential Smoothing and Holt-wintry weather models and the performance of the fashion forecast were judged using the accuracy level of each symmetric loss factor and asymmetric used rectangular (MSE) errors, mean Total Deviations (MAD) and mean Total percentage errors (MAPE). From a precision rating, a double slider version of the interpreter can be used to anticipate and smooth out a series of currency exchange rates with three different versions. In an effort to test several models of the Akaike information Criterion (AIC) small currency, we have examined the Autoregressive version that incorporates conventional change (ARIMA) that can be used to anticipate the change in funding for the South Asian Local Cooperation (SAARC). This research allows for the discovery of different strategies and reduces the type of human intelligence which ultimately leads to good health.

Keywords

• Forecasting
• South Asian Association for Regional Cooperation (SAARC)
• Akaike Information Criterion (AIC)
• Autoregressive Integrated Moving Average (ARIMA)