Comparison of Regression and Neural Network for Demand Forecasting |
Author(s): |
| Amit Sharma , Om Institute of Technology and Management, Hisar; Deepak Kumar, Om Institute of Technology and Management, Hisar |
Keywords: |
| Forecasting of energy consumption, Neural Networks, Regression Analysis, Forecasting Model, Prediction Error |
Abstract |
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Forecasting of power consumption and planning of the balances of electric power maybe said to be main objective of management. The amount of energy consumption defines the structure of generating equipment electric network configuration, the production of electric and thermal energy, use of energy resources, reliability of power supply ,the quality of electric power .the planning accuracy is an actual task and it depends upon calculation method. This work shows a comparative analysis of regressive and neural network model for the solution of a problem of forecasting of daily power consumption. The result shows that NN provide accurate prediction outperforming three state of the art approaches and a number of base line. NN is also more accurate and efficient than a non-iterative version approach (regression method). |
Other Details |
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Paper ID: IJSRDV9I20305 Published in: Volume : 9, Issue : 2 Publication Date: 01/05/2021 Page(s): 499-505 |
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