A Predictive Analytic Time Series Forecasting Model

Abstract

Predictive Analytics is the process of using predictive modelling techniques to analyse the various types of data in agriculture, business management, engineering, weather forecasting, planning, meteorology etc. Most frequently using predictive modelling technique in Electrical load forecasting and Agricultural production forecasting is the time series forecasting technique. Particularly, in the electrical systems, the future electric load demand and peak load can be predicted by using several methods such as regression methods and time series methods; data science methods namely ML, DL, SVM, ANN, AI techniques etc. In the empirical study, a time series forecasting technique based on a selected ARIMA (1,1,2) model has been applied to an agricultural big data and obtained forecasts for Bengal gram average monthly prices of Andhra Pradesh state, India from Jan’2023 to Dec’2025. In the similar lines, the proposed time series forecasting modelling can be applied to forecast short term electric load demand by using the given previous bigdata.