The kernel recursive least-squares algorithm
By: Researcher
Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).
Please contact us in case of a broken link from here
| Authors | Y. Engel, Shie Mannor, R. Meir |
| Journal/Conference Name | IEEE Transactions on Signal Processing |
| Paper Category | Signal Processing |
| Paper Abstract | This paper presents a new approach for short-term load forecasting problem based on the kernel recursive least-square algorithm (KRLS). The kernel recursive least-square algorithm is an online real-time kernel-based algorithm and also capable of efficiently solving in recursive manner nonlinear least-square predictive problems. In this paper we consider the loads as a time series, through training the KRLS, we give the one-step ahead load forecasting. The test result of short term load forecasting series shows that the precision of load forecasting is greatly improved by means of the new method. |
| Date of publication | 2010 |
| Code Programming Language | Julia |
| Comment |
Copyright Researcher 2022