TY  - JOUR
T1  - PSO Based Combinations of ANNs for  Short Term-Daily Peak Load Forecasting
AU - , P. Subbaraj AU - , V. Rajasekaran 
JO  - Asian Journal of Information Technology
VL  - 6
IS  - 2
SP  - 154
EP  - 159
PY  - 2007
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2007.154.159
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2007.154.159
KW  - Combination of artificial neural network
KW  -short term-daily peak load forecasting
KW  -particle swarm optimization
AB  - This study presents a new approach for short term - daily peak load forecasting using Particle Swarm Optimization based Combinations of Artificial Neural Network (PSOCANN) modules. In this study, a set of neural networks has been trained with different architecture and with different training parameters. The Artificial Neural Networks (ANNs) are trained and tested for the actual load data of Chennai city (India). A method of optimal linear combination is used to combine selected networks to produce better results, rather than using a single best trained ANN. The obtained test results indicate that the proposed method of approach improves the accuracy of the load forecasting.
ER  -