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http://hdl.handle.net/2080/70Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dash, P K | - |
| dc.contributor.author | Liew, A C | - |
| dc.contributor.author | Rahman, S | - |
| dc.date.accessioned | 2005-06-28T09:01:39Z | - |
| dc.date.available | 2005-06-28T09:01:39Z | - |
| dc.date.issued | 1996-01 | - |
| dc.identifier.citation | IEE Proceedings-Generation, Transmission and Distribution, Vol 143, Iss 1, P 106-114 | en |
| dc.identifier.uri | http://hdl.handle.net/2080/70 | - |
| dc.description | Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEE. | en |
| dc.description.abstract | A hybrid neural network fuzzy expert system is developed to forecast short-term electric load accurately. The fuzzy membership values of the load and other weather variables are the inputs to the neural network, and the output comprises the membership values of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and fuzzy inference mechanism. Extensive studies have been performed for all seasons, and a few examples are presented in the paper, average, peak and hourly load forecasts | en |
| dc.format.extent | 873522 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en | - |
| dc.publisher | IEE | en |
| dc.subject | expert systems | en |
| dc.subject | fuzzy neural nets | en |
| dc.subject | load forecasting | en |
| dc.title | Fuzzy neural network and fuzzy expert system for load forecasting | en |
| dc.type | Article | en |
| Appears in Collections: | Journal Articles | |
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