ELECTRICITY DEMAND FORECASTING FOR KARNATAKA STATE USING ARIMA MODEL |
Author(s): |
Padmaja K |
Keywords: |
Autoregressive Integrated Moving Average (ARIMA), Electricity demand forecasting, Big data. |
Abstract |
In the current era abundance of data is available and this data is being overloaded every second, minute, hour, day, week, month and years etc. Organizations have taken initiative to process this mammal amount of data to explore the ability in making critical and crucial decisions of the company. These decisions will help the organization to identify minimize possible risks, opportunities and cost control etc. Big data analytics is the process of handling and managing large amount of diverse data, but it also has the ability to question itself on the data available, by applying new methods, algorithms and producing new results which help the organization to make useful decisions. It produces useful information, patterns that are hidden, and many hidden correlations. It also helps in predicting and forecasting the future and benefits the business of the organization, and also organizations can make the planning’s of their business more effectively and better implemented to avoid the loss of their business in their organization. Autoregressive Integrated Moving Average (ARIMA) model is used to forecast power supply for the city of Karanataka State. Using this technology, Electricity demand forecasting for Karanataka State is predicted. |
Other Details |
Paper ID: IJSARTV Published in: Volume : 2, Issue : 11 Publication Date: 11/7/2016 |
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