Publicacoes - INESC TEC

Publicações

Publicações por LIAAD

2009

Advanced Data Mining and Applications, 5th International Conference, ADMA 2009, Beijing, China, August 17-19, 2009. Proceedings

Autores
Huang, R; Yang, Q; Pei, J; Gama, J; Meng, X; Li, X;

Publicação
ADMA

Abstract

2009

Data Streams

Autores
Gama, J; Rodrigues, PP;

Publicação
Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes)

Abstract

2009

Learning from Data Streams

Autores
Gama, J; Rodrigues, PP;

Publicação
Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes)

Abstract

2009

Special track on data streams

Autores
Gama, J; Carvalho, A; Rodrigues, PP; Aguilar, J;

Publicação
Proceedings of the ACM Symposium on Applied Computing

Abstract

2009

Advanced Data Mining and Applications: 5th International Conference, ADMA 2009 Beijing, China, August 17-19, 2009 Proceedings - Preface

Autores
Qiang, Y; Ronghuai, H; Jian, P; Gama, J; Xiaofeng, M;

Publicação
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

2009

Entropy and Correntropy Against Minimum Square Error in Offline and Online Three-Day Ahead Wind Power Forecasting

Autores
Bessa, RJ; Miranda, V; Gama, J;

Publicação
IEEE TRANSACTIONS ON POWER SYSTEMS

Abstract
This paper reports new results in adopting entropy concepts to the training of neural networks to perform wind power prediction as a function of wind characteristics (speed and direction) in wind parks connected to a power grid. Renyi's entropy is combined with a Parzen windows estimation of the error pdf to form the basis of two criteria (minimum entropy and maximum correntropy) under which neural networks are trained. The results are favorably compared in online and offline training with the traditional minimum square error (MSE) criterion. Real case examples for two distinct wind parks are presented.

FecharLer Abstract