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SOFSEM
2004
Springer
15 years 5 months ago
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Matej Makula, Michal Cernanský, Lubica Benu...
IWANN
2007
Springer
15 years 5 months ago
A Novel 2-D Model Approach for the Prediction of Hourly Solar Radiation
In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year...
Fatih Onur Hocaoglu, Ömer Nezih Gerek, Mehmet...
AI
2002
Springer
14 years 11 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
IEAAIE
2005
Springer
15 years 5 months ago
Movement Prediction from Real-World Images Using a Liquid State Machine
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Harald Burgsteiner, Mark Kröll, Alexander Leo...
ICCS
2005
Springer
15 years 5 months ago
Adaptive Smoothing Neural Networks in Foreign Exchange Rate Forecasting
This study proposes a novel forecasting approach – an adaptive smoothing neural network (ASNN) – to predict foreign exchange rates. In this new model, adaptive smoothing techni...
Lean Yu, Shouyang Wang, Kin Keung Lai