While the Covid-19 epidemic in world was not over yet, monkeypox started. The virus spread to more than 59 countries 4 months. Computer-aided forecasting models are needed effectively control this spread. It has been seen previous outbreaks that time-series effective estimating impact of and taking necessary precautions. In study, different Automatic Regressive Integrated Moving Average (ARIMA)...

FinTech companies have emerged as a new force in the financial industry recent years. Their innovative business models, high growth performance, and broad market prospects attracted attention pursuit of numerous investors. Therefore, predicting future trend company stocks is significant for This paper selects PayPal prediction target, collects closing prices from 2018 to 2023, uses Auto-regress...

• Traditional approaches, including Box–Jenkins autoregressive integrated moving average (ARIMA) model, autoregressive and moving average with exogenous variables (ARMAX) model, seasonal autoregressive integrated moving average (SARIMA) model, exponential smoothing models [including Holt–Winters model (HW) and seasonal Holt and Winters’ linear exponential smoothing (SHW)], state space/Kalman fi...

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...

Abstract Life expectancy at birth (LEB) is a major factor for decision-making bodies when developing new healthcare policies or improving existing ones. This paper, with the help of R language, processes and examine LEB data in Saudi Arabia from 1960 to 2012 using time-series analysis. To test validity model, 2013 2018 are used. The performance selected auto regressive integrated moving average...

Februari 2020 merupakan waktu awal warga Indonesia didiagnosa positif Covid-19. Hingga kini, penyakit yang dikarenakan oleh Virus Corona ini belum mereda, bahkan dinyatakan sebagai Pandemi Global. Tujuan penelitian adalah mencari model prediksi Time Series untuk jumlah kasus Covid-19 di salah satu kota dengan infeksi terbsesar yaitu Jakarta. Penelitian menggunakan data dari Open Data Jakarta re...

This study develops a sedimentation process model that simulate the effects of inflow water quality, treatment flow rate and outflow water quality. The model uses transfer function ARIMA (Auto-Regressive Moving Average) for reflecting the dynamic characteristics of the system The sedimentation model for outflow water turbidity are separated into low and high turbidity by input variables, turbid...

As modern vehicles system becomes increasingly complex, there is an urgent need to develop a framework monitor the behavior and detect unhealthy states appropriately arrange maintenance in order extend vehicle life cycle. Sensors installed are able record huge amount of multiple channel time series data. This paper develops prediction model state detection strategy for monitoring operating by a...

In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, analyze the effect of on two main aspects life: exclusion and life satisfaction. First, predict rates Auto Regressive Integrated Moving Average (ARIMA) model results are further used in a linear regression alongside satisfaction data, thus obtaining hybrid model. With help...

Drought forecasting plays a crucial role in drought mitigation actions. Thus, this research deals with linear stochastic models (autoregressive integrated moving average (ARIMA)) as a suitable tool to forecast drought. Several ARIMA models are developed for drought forecasting using the Standardized Precipitation Evapotranspiration Index (SPEI) in a hyper-arid climate. The results reveal that a...