Results 1 
7 of
7
Multiresolution FIR NeuralNetworkBased Learning Algorithm Applied to Network Traffic Prediction
 IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Review
, 2006
"... Abstract—In this paper, a multiresolution finiteimpulseresponse (FIR) neuralnetworkbased learning algorithm using the maximal overlap discrete wavelet transform (MODWT) is proposed. The multiresolution learning algorithm employs the analysis framework of wavelet theory, which decomposes a signal ..."
Abstract

Cited by 8 (5 self)
 Add to MetaCart
(Show Context)
Abstract—In this paper, a multiresolution finiteimpulseresponse (FIR) neuralnetworkbased learning algorithm using the maximal overlap discrete wavelet transform (MODWT) is proposed. The multiresolution learning algorithm employs the analysis framework of wavelet theory, which decomposes a signal into wavelet coefficients and scaling coefficients. The translationinvariant property of the MODWT allows aligment of events in a multiresolution analysis with respect to the original time series and, therefore, preserving the integrity of some transient events. A learning algorithm is also derived for adapting the gain of the activation functions at each level of resolution. The proposed multiresolution FIR neuralnetworkbased learning algorithm is applied to network traffic prediction (realworld aggregate Ethernet traffic data) with comparable results. These results indicate that the generalization ability of the FIR neural network is improved by the proposed multiresolution learning algorithm. Index Terms—Finiteimpulseresponse (FIR) neural networks, multiresolution learning, network traffic prediction, wavelet transforms, wavelets. I.
An Application of Pruning in the Design of Neural Networks for Real Time Flood Forecasting
, 2005
"... We propose the application of pruning in the design of neural networks for hydrological prediction. The basic idea of pruning algorithms, which have not been used in water resources problems yet, is to start from a network which is larger than necessary, and then remove the parameters that are le ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
We propose the application of pruning in the design of neural networks for hydrological prediction. The basic idea of pruning algorithms, which have not been used in water resources problems yet, is to start from a network which is larger than necessary, and then remove the parameters that are less influential one at a time, designing a much more parameterparsimonious model. We compare pruned and complete predictors on two quite different Italian catchments. Remarkably, pruned models may provide better generalization than fully connected ones, thus improving the quality of the forecast.
ORIGINAL ARTICLE
"... Abstract We propose the application of pruning in the design of neural networks for hydrological prediction. The basic idea of pruning algorithms, which have not been used in water resources problems yet, is to start from a network which is larger than necessary, and then remove the parameters that ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract We propose the application of pruning in the design of neural networks for hydrological prediction. The basic idea of pruning algorithms, which have not been used in water resources problems yet, is to start from a network which is larger than necessary, and then remove the parameters that are less influential one at a time, designing a much more parameterparsimonious model. We compare pruned and complete predictors on two quite different Italian catchments. Remarkably, pruned models may provide better generalization than fully connected ones, thus improving the quality of the forecast. Besides the performance issues, pruning is useful to provide evidence of inputs relevance, removing measuring stations identified as redundant (30–40 % in our case studies) from the input set. This is a desirable property in the system exercise since data may not be available in extreme situations such as floods; the smaller the set of measuring stations the model depends on, the lower the probability of system downtimes due to missing data. Furthermore, the Authority in charge of the forecast system may decide for realtime operations just to link the gauges of the pruned predictor, thus saving costs considerably, a critical issue in developing countries.
Coupling Fuzzy Modelling and Neural Networks for River Flood Prediction
, 2005
"... Over the last decade, neural networksbased flood forecasts systems have been increasingly used in the hydrological research. Usually, input data of the network are composed by past measurements of flows and rainfalls, without providing a description of the saturation state of the basin, which in ..."
Abstract
 Add to MetaCart
(Show Context)
Over the last decade, neural networksbased flood forecasts systems have been increasingly used in the hydrological research. Usually, input data of the network are composed by past measurements of flows and rainfalls, without providing a description of the saturation state of the basin, which in contrast plays a key role in the rainfallrunoff process. This paper couples neural networks and fuzzy logic in order to enrich the description of the basin saturation state for flood forecasting purposes.
Computational Intelligence in Weather Forecasting: A Review
"... Abstract: Since 1990s, computational intelligence models have been widely used in several applications of weather forecasting. Thanks to their ability to have powerful pattern classification and pattern recognition capabilities. This paper presents an overview of using the various computational inte ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract: Since 1990s, computational intelligence models have been widely used in several applications of weather forecasting. Thanks to their ability to have powerful pattern classification and pattern recognition capabilities. This paper presents an overview of using the various computational intelligence tools in weather forecasting, describing the main contributions on this field and providing taxonomy of the existing proposals according to the type of tools used.
Article Performance Prediction of Differential Fibers with a BiDirectional Optimization Approach
, 2013
"... www.mdpi.com/journal/materials ..."
(Show Context)
CONCEPTION D’UNE NOUVELLE STRATEGIE
"... présenté à l’École Nationale d’Ingénieurs de Sfax en vue de l’obtention du MASTERE ..."
Abstract
 Add to MetaCart
présenté à l’École Nationale d’Ingénieurs de Sfax en vue de l’obtention du MASTERE