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A neurofuzzy network knowledge extraction and extended gram-schmidt algorithm for model subspace decomposition

Xia Hong, C.J. Harris
2003 IEEE transactions on fuzzy systems  
The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism.  ...  Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.  ...  Numerical examples have demonstrated the effectiveness of the new algorithm.  ... 
doi:10.1109/tfuzz.2003.814842 fatcat:jx4zimhvwbfblpj3637zipx5pm

Sequential learning in neural networks: A review and a discussion of pseudorehearsal based methods

Anthony Robins
2004 Intelligent Data Analysis  
Most neural networks handle this kind of task very badly, as new learning completely disrupts information previously learned by the network.  ...  In particular, we review the literature relating to the pseudorehearsal mechanism, which is an effective solution to the catastrophic forgetting problem in back propagation type networks.  ...  Acknowledgments Parts of this paper were written while the author was on study leave. Many thanks to Bob  ... 
doi:10.3233/ida-2004-8306 fatcat:tcx4rqdubfhphpn4jhxpx7nh3y

Robust Neurofuzzy Rule Base Knowledge Extraction and Estimation Using Subspace Decomposition Combined With Regularization and D-Optimality

X. Hong, C.J. Harris, S. Chen
2004 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.  ...  A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules.  ...  decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules [22] , which, based on a T-S inference mechanism, establishes a one to one mapping  ... 
doi:10.1109/tsmcb.2003.817089 pmid:15369096 fatcat:2y3klf4eqzfubhozvy77oebvwu

Inquiring Organisations

James Courtney, David Croasdell, David Paradice
1998 Australasian Journal of Information Systems  
This paper explores the relationship between inquiry and learning in organisations and how information technology can be used to support the process of knowledge creation in the context of inquiring systems  ...  Churchman (1971) developed five archetypal models of inquiring systems in an effort to expand the field of management information systems along a philosophical path.  ...  One of the most distinctive features of inquiring systems design is the inclusion of elaborate mechanisms for "guaranteeing" that only "valid" knowledge is produced. Such a concept is not new.  ... 
doi:10.3127/ajis.v6i1.313 fatcat:aqyg4cbuv5g77jgkgnze4o6slu

An implementation and empirical evaluation of an exploration environment with different tutoring strategies

Franz Schmalhofer, Otto Kühn, Rhona Charron, Paula Messamer
1990 Behavoir research methods, instruments & computers  
An exploration environment and tutoring strategies were developed for the first few hours of learning the programming language LISP.  ...  In this environment, the amount of exploratory and receptive learning can be systematically manipulated.  ...  The generated inputs are evaluated by the LISP interpreter, and either the result of the evaluation or an error message is displayed.  ... 
doi:10.3758/bf03203142 fatcat:tewh3662fjfmdjxjdc6scxdpcq


2009 Advances in Complex Systems  
In this way the context is interpreted in terms of the concurrent low-level learning mechanism.  ...  While the low-level adaptation continues to follow a set of rigid learning rules, the second-order learning modulates the elementary behaviors and affects the distribution of the sensory inputs via the  ...  Acknowledgment This work was supported by the BMBF in the framework of the Bernstein Centers for Computational Neuroscience, grant number 01GQ0432. Discussions with C. Kolodziejski and G.  ... 
doi:10.1142/s0219525909002258 fatcat:slsf2lgbfvhfxhqufeejijmnt4

A Spatio-Temporal Spot-Forecasting Framework for Urban Traffic Prediction [article]

Rodrigo de Medrano, José L. Aznarte
2020 arXiv   pre-print
Through extensive experimentation, we show how the results of our approach are stable and better than those of other state-of-the-art alternatives.  ...  Our proposal is based on an interpretable attention-based neural network in which several modules are combined in order to capture key spatio-temporal time series components.  ...  ACKNOWLEDGEMENTS This research has been partially funded by the Empresa Municipal de Transportes (EMT) of Madrid under the program "Aula Universitaria EMT/UNED de Calidad del Aire y Movilidad Sostenible  ... 
arXiv:2003.13977v2 fatcat:rtipocx6fzabxgp4xwubzqz5aq

Perpetual Learning Framework based on Type-2 Fuzzy Logic System for a Complex Manufacturing Process

Ali Baraka, George Panoutsos, Stephen Cater
2016 IFAC-PapersOnLine  
The proposed method relies on the creation of new fuzzy rules which are updated and optimised during the incremental learning process.  ...  The 'perpetual' property refers to the capability of the proposed system to continuously learn from new process data, in an incremental learning fashion.  ...  UK for the financial support and for providing expert knowledge and data for the case study, and also The University of Sheffield for the financial support.  ... 
doi:10.1016/j.ifacol.2016.10.111 fatcat:wmwsnf65d5c2dcnrih4l3r63w4

Ranfis : Rough Adaptive Neuro-Fuzzy Inference System

Sandeep Chandana, Rene V. Mayorga
2007 Zenodo  
The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function.  ...  The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology.  ...  World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering Vol :1, No:12, 2007  ... 
doi:10.5281/zenodo.1078279 fatcat:qgrjdf6kdbed7porto74jvlnbq

The Idea of Knowledge Supplementation and Explanation Using Neural Networks to Support Decisions in Construction Engineering

Marcin Gajzler
2013 Procedia Engineering  
This method effectively supports the process of construction of advisory systems.  ...  The article presents the problem of knowledge in knowledge-based systems, such as advisory systems used in construction engineering.  ...  In the author's opinion, the probability depends on the size of the errors occurring in the network in the learning and verification processes and if such errors are minimized in the learning process and  ... 
doi:10.1016/j.proeng.2013.04.041 fatcat:45qbgr7ku5ds3foxvmcgetzvl4

Modeling and Predicting Popularity Dynamics via Deep Learning Attention Mechanism [article]

Sha Yuan, Yu Zhang, Jie Tang, Huawei Shen, Xingxing Wei
2018 arXiv   pre-print
Extensive experiments on a real-large citation data set demonstrate that the designed deep learning attention mechanism possesses remarkable power at predicting the long-term popularity dynamics.  ...  An ability to predict the popularity dynamics of individual items within a complex evolving system has important implications in a wide range of domains.  ...  Broadly, attention mechanisms are components of prediction systems that allow the system to sequentially focus on different subsets of the input (Cho, Courville, and Bengio 2015) .  ... 
arXiv:1811.02117v1 fatcat:ixcceatqorbszinpoqi6vnstuq

Categories, prototypes and memory systems in Alzheimer's disease

Szabolcs Kéri, Zoltán Janka, György Benedek, Péter Aszalós, Botond Szatmáry, Gábor Szirtes, András Lörincz
2002 Trends in Cognitive Sciences  
Simple, self-organizing neuronal networks can explain prototype learning and related dysfunctions in Alzheimer's disease, and provide a model of how prototype learning is mediated by circumscribed mechanisms  ...  Recent studies indicate that category learning is mediated by multiple neuronal systems.  ...  Behavior of the model Working and learning phases are as follows [g] . A well-tuned system for input from the training set reconstructs the input in one cycle.  ... 
doi:10.1016/s1364-6613(00)01859-3 pmid:11861191 fatcat:drx7cpqikncltnylimdghcahvm

Evolving to learn: discovering interpretable plasticity rules for spiking networks [article]

Jakob Jordan, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici
2021 arXiv   pre-print
We suggest an automated approach for discovering biophysically plausible plasticity rules based on the definition of task families, associated performance measures and biophysical constraints.  ...  We successfully apply our approach to typical learning scenarios and discover previously unknown mechanisms for learning efficiently from rewards, recover efficient gradient-descent methods for learning  ...  In addition, the distributed, implicit representation of plasticity rules in HyperNEAT can be difficult to interpret, which hinders a deeper understanding of the learning mechanisms.  ... 
arXiv:2005.14149v3 fatcat:qcee6al52nee3gnmevv3is3s4q

Evaluation of Detection System of Fault Attacks based on Neural Network into a Java Virtual Machine

Ilhame El farissi, Mostafa AZIZI, Jean-Louis Lanet, Mimoun Moussaoui
But, the fault attacks based on the variation of the physical parameters are able to disrupt its operation.  ...  In this context, the detection rate of the attacks is 96% with no false positive.  ...  And as it was possible to integrate the Java virtual machine, we can enhance the security of the system of smart card by a Neural Network.  ... 
doi:10.24297/ijct.v10i3.3278 fatcat:oktjrk5vmjb77cxm42nwn622xy

Social symbol grounding and language evolution

2007 Interaction Studies  
A preliminary experiment is presented in which we investigate the effect of a number of learning mechanisms.  ...  We discuss how we can simulate language evolution in a relatively complex environment which has been developed in the context of the New Ties project.  ...  Opinions and errors in this manuscript are the authors' responsibility, they do not necessarily reflect those of the EC or other New Ties members.  ... 
doi:10.1075/is.8.1.04vog fatcat:whnch7nb55ewpiv6glcfyizmny
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