An optimized fuzzy time series analysis for predicting electricity consumption using ARIMA model.

Foreseeing Electricity value utilization is the primary part of energy management, the sustenance which streamlines the inhabitants solace by subsiding the energy use. This paper proposes essence of ARIMA model which is utilized to figure the pinnacle utilization of power with different perspectives like irregularity, stable and autocorrelation of time series into thought. Autoregressive Integrated Moving Average Model (ARIMA) is a class of verifiable models for taking apart and expecting time series data. It unequivocally considers a set-up of standard plans in time series data, and as such gives a clear by and by staggering technique for making skilful time series realities. The three ARIMA models, which are very prodigious and energetic to foster a dependable model, are explored to conjecture power utilization for giving the necessary degree of execution. The built-in model is feasible to execute solid methodology and organize static forecast execution. The authentic monthly Area costs dataset from Energy power markets were considered over 12 month time period of 11years time block was taken into consideration to visualize the trend. [ABSTRACT FROM AUTHOR]