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A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
- IEEE Transactions on Systems, Man and Cybernetics, Part B
"... Abstract—An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization (PSO ..."
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Cited by 79 (2 self)
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Abstract—An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization
River Flow Forecasting using Recurrent Neural Networks
- Water Resour. Manage
, 2004
"... Forecasting a hydrologic time series has been one of the most complicated tasks owing to the wide range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently, Artificial Neural Networks (ANNs) have become quite popula ..."
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Cited by 8 (0 self)
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. In addition, the size of the architecture and the training time required were less for the recurrent neural networks. The recurrent neural network gave better results for both single step ahead and multiple step ahead forecasting. Hence recurrent neural networks are recommended as a tool for river flow
Recurrent Neural Networks for Customer Purchase Prediction on Twitter
"... ABSTRACT The abundance of data posted to Twitter enables companies to extract useful information, such as Twitter users who are dissatisfied with a product. We endeavor to determine which Twitter users are potential customers for companies and would be receptive to product recommendations through t ..."
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, eventually bought the product. For the relevance task, among four models, a feed-forward neural network yielded the best cross-validation accuracy of over 80% per product. For customer purchase prediction of a product, we observed improved performance with the use of sequential input of tweets to recurrent
Group Selection by Using Lotka-Volterra Recurrent Neural Networks
"... Abstract-This paper studies the problem of group selection by using Lotka-Volterra recurrent neural networks. The networks are required to be with self-inhibition and lateral inhibition. The group selection is based on the concepts of permitted and forbidden sets. By restricting the strength of the ..."
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Abstract-This paper studies the problem of group selection by using Lotka-Volterra recurrent neural networks. The networks are required to be with self-inhibition and lateral inhibition. The group selection is based on the concepts of permitted and forbidden sets. By restricting the strength
Contour Segmentation with Recurrent Neural Networks of Pulse-Coding Neurons
- In: Sommer, Daniilidis, Pauli: Computer Analysis of Images and Patterns, CAIP
, 1997
"... . The performance of technical and biological vision systems crucially relies on powerful processing capabilities. Robust object recognition must be based on representations of segmented object candidates which are kept stable and sparse despite the highly variable nature of the environment. Here, w ..."
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Cited by 12 (0 self)
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, we propose a network of pulse-coding neurons based on biological principles which establishs such representations using contour information. The system solves the task of grouping and figureground segregation by creating flexible temporal correlations among contour extracting units. In contrast
Ask Me Any Rating: A Content-based Recommender System based on Recurrent Neural Networks
"... Abstract. In this work we propose Ask Me Any Rating (AMAR), a novel content-based recommender system based on deep neural networks which is able to produce top-N recommendations leveraging user and item embeddings which are learnt from textual information describing the items. A comprehensive exper ..."
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Cited by 1 (1 self)
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Abstract. In this work we propose Ask Me Any Rating (AMAR), a novel content-based recommender system based on deep neural networks which is able to produce top-N recommendations leveraging user and item embeddings which are learnt from textual information describing the items. A comprehensive
A population density approach that facilitates large-scale modeling of neural networks: Analysis and an application to orientation tuning
- J. Comp. Neurosci
, 2000
"... We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are grouped into large populations of similar neurons. For each population, we form a probability density which represents th ..."
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Cited by 61 (2 self)
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-integral equation which we solve numerically. Results obtained for several example networks are tested against conventional computations for groups of individual neurons. We apply this approach to modeling orientation tuning in the visual cortex. Our population density model is based on the recurrent feedback model
RESEARCH ARTICLE Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks
"... The processing of a visual stimulus can be subdivided into a number of stages. Upon stimu-lus presentation there is an early phase of feedforward processing where the visual informa-tion is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This i ..."
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activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mech
Recurrent network activity drives striatal synaptogenesis. Nature
, 2012
"... Neural activity during development critically shapes postnatal wiring of the mammalian brain. This is best illustrated by the sensory systems, in which the patterned feed-forward excitation provided by sensory organs and experience drives the formation of mature topographic circuits capable of extra ..."
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Cited by 6 (1 self)
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of extracting specific features of sensory stimuli1,2. In contrast, little is known about the role of early activity in the development of the basal ganglia, a phylogenetically ancient group of nuclei fundamentally important for complex motor action and reward-based learning3,4. These nuclei lack direct sensory
Recurrent Neural Network based Boolean Factor Analysis and Its Application to Word Clustering
- IEEE Transactions on Neural Networks
, 2009
"... The paper describes an automatic document concepts searching metod based on recurrent neural network implementation of Bolean factor analysis procedure. Advanatge of this approach is the ability of effective anlysiss of large natural lenguage databases, with rich vocabulary and easy concepts update. ..."
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Cited by 2 (0 self)
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The paper describes an automatic document concepts searching metod based on recurrent neural network implementation of Bolean factor analysis procedure. Advanatge of this approach is the ability of effective anlysiss of large natural lenguage databases, with rich vocabulary and easy concepts update
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