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FLAIRS
2004
8 years 7 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
CNSR
2004
IEEE
174views Communications» more  CNSR 2004»
8 years 10 months ago
Network Intrusion Detection Using an Improved Competitive Learning Neural Network
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...
John Zhong Lei, Ali A. Ghorbani
ISNN
2011
Springer
7 years 9 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classiļ¬cation. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
IJACTAICIT
2010
153views more  IJACTAICIT 2010»
8 years 1 months ago
Prediction Using Recurrent Neural Network Based Fuzzy Inference system by the Modified Bees Algorithm
In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
Zahra Khanmirzaei, Mohammad Teshnehlab
ECAI
2004
Springer
8 years 11 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
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