| dc.contributor.author | Param, Sowjanya | |
| dc.description.abstract | As the economy is growing, electricity usage has been growing and to meet the needs of energy market in providing the electricity without power outages, utility companies, distributors and investors need a powerful tool that can effectively predict electricity demand day ahead that can help them in making better decisions in inventory planning, power generation, and resource management. Historical data is a great source that can be used with artificial neural networks to predict electricity demand effectively with a decent error rate of 0.06. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Electricity Demand Prediction Using Artificial Neural Network Framework | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2015-08-10T20:56:27Z | |
| dc.date.available | 2015-08-10T20:56:27Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | http://hdl.handle.net/10365/25233 | |
| dc.subject.lcsh | Electric power consumption -- Forecasting -- Mathematical models. | en_US |
| dc.subject.lcsh | Neural networks (Computer science) | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Nygard, Kendall | |
