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Training Recurrent Neural Networks Using Optimization Layer-by- Layer Recursive Least Squares Algorithm for Vibration Signals System Identification and Fault Diagnostic Analysis

S.-Y. Cho, T.W.S. Chow, Y. Fang
2001 Journal of Intelligent Systems  
Depending on the representation ability and the dynamic capability of recurrent neural networks for nonlinear models, a neural-based approach for general practical nonlinear systems identification is demonstrated  ...  The proposed neural-based approach is also applied to the railway carriage system identification by identifying the train vibration signal.  ...  In accordance with this property, a railway carriage system identification based on a neural network model is valuable for an on-line railway carriage conditions monitoring system.  ... 
doi:10.1515/jisys.2001.11.2.125 fatcat:lbggmojourbmdewez23kfbyjym

A Levitation Condition Awareness Architecture for Low-Speed Maglev Train Based on Data-Driven Random Matrix Analysis

Yuanzhe Zhao, Fei Peng, Linjie Ren, Guobin Lin, Junqi Xu
2020 IEEE Access  
are further considered in some studies based on the identification of nonlinear neural networks [30, 31] .  ...  Training is performed with the series-parallel architecture using NARX, so that input to the feedforward network is more accurate and that the resulting network has a purely feedforward architecture for  ... 
doi:10.1109/access.2020.3025968 fatcat:utk5wpds3vfdpce52vuhsxsohe

Approaches to Dealing with Missing Data in Railway Asset Management

P. McMahon, T. Zhang, R. Dwight
2020 IEEE Access  
Through making comparisons among these models and algorithms, a procedure is proposed to guide selecting the appropriate models based on different data missing scenarios.  ...  Through making comparisons among these models and algorithms, a procedure is proposed to guide selecting the appropriate models based on different data missing scenarios.  ...  ACKNOWLEDGMENT The authors are grateful to the two anonymous reviewers for their careful reading and constructive comments on an earlier version of this article.  ... 
doi:10.1109/access.2020.2978902 fatcat:vqefhjgw6fdrralqt6a7r53yyq

Handwritten Digits Recognition Using SVM, KNN, RF and Deep Learning Neural Networks

Yevhen Chychkarov, Anastasiia Serhiienko, Iryna Syrmamiikh, Anatolii Kargin
2021 Computer Modeling and Intelligent Systems  
For recognition, each image of a digit was converted to a 28x28 size and fed to the input of a pre-trained neural network.  ...  To construct and train neural networks or train classifiers, a well-known and rather complete base of handwritten digits MNIST was chosen.  ...  A multilayer perceptron is a class of feedforward artificial neural networks that consists of at least three layers: input, hidden, and output.  ... 
doi:10.32782/cmis/2864-44 fatcat:5o7ibuc6pzc5hick2kxxe5ohci

Control Valve Stiction Identification, Modelling, Quantification and Control - A Review

Srinivasan Arumugam, Rames C. Panda
2011 Sensors & Transducers  
in this field, so that readers can invent their goals for future research work on nonlinear systems identification and control.  ...  Understanding nonlinear behaviour of control valves in order to maintain the quality of the end products in the industry, this review article surveys the identification, modelling, estimation and design  ...  Zabiri et al [29] developed the quantification algorithm for stiction based on Feedforward-Back-propagation NN and recurrent NN, as well as Elman and Layer Recurrent Networks and Cascade neural network  ... 
doaj:ba42d31c57394264b4843e7dbe1b5fbd fatcat:vrxwcvcyzvfkrbz4rzpcvyqvxe

Certifying Unstability of Switched Systems Using Sum of Squares Programming

Benoît Legat, Pablo Parrilo, Raphaël Jungers
2020 SIAM Journal of Control and Optimization  
Acknowledgements We argue that, from a modeling point of view, the assumptions of distinct timescales is ubiquitous when modeling complex systems.  ...  This alternative way of analysis of slow-fast systems with particular structure may lead to a later analysis of multi-timescale systems over networks.  ...  A NLMPC scheme with feedforward neural networks as predictive model, was useful for denitrification process [3] .  ... 
doi:10.1137/18m1173460 fatcat:ytlzbwk7vbampbuyo6snenz33m

A generic fault detection and diagnosis approach for railway assets

Hao Bai, C. Roberts, C. Goodman
2008 IET International Conference on Railway Engineering 2008 (ICRE 2008)   unpublished
The railway assets studied in this project, are those widely distributed pieces of equipment that are critical to the dependable operation of the railway system.  ...  Finally, a new three level architecture for railway condition monitoring is discussed for practical applications.  ...  Andy Dunn for his technical support and contribution to my lab work. Thanks to Mr. Rhys Davies for his support to my working environment in the office.  ... 
doi:10.1049/ic:20080031 fatcat:dsnfojpyqnhmda4gz5sij3yowe

Abstract Selection

1992 Journal of Laryngology and Otology  
Selection Powder administration of pure budesonide for the treatment of seasonal allergic rhinitis.  ...  We conclude that budesonide, delivered as pure powder from a multidose dispenser, is effective and safe for the treatment of seasonal allergic rhinitis.  ...  From a network model of the cat middle-ear cavities we estimate the contributions of pressures on the cochlear windows for both normal and abnormal cat ears.  ... 
doi:10.1017/s0022215100120195 fatcat:aspb3mrndjhu7gbsqubyvkwzrq

Learning driving patterns to support navigation [article]

Dijan Mitrović, University Of Canterbury
Here we also present the new method for driving event recognition based on hidden Markov models.  ...  We found that all neural network architectures have good performances for short-term vehicle movement prediction.  ...  Neural network weights could be preset to allow for different input ranges.  ... 
doi:10.26021/2033 fatcat:hxzc7reo5rddfar3r7bphpyh5a

European Transport \ Trasporti Europei Editorial Advisory Board Editor-in-chief/Direttore responsabile: European Transport \ Trasporti Europei

Giacomo Borruso, Aurelio Amodeo, Michel Bierlaire, Sergio Caracoglia, Roberto Camus, Marino De Luca, Jadranka Jović, Enrico Musso, Esko Staresearch, Finland Helsinki, Stratos Papadimitriou, Piet Rietveld (+7 others)
Federico Rupi for their precious suggestions. Thanks also to Mr Marco Comani, Head of the Network and Fleet Planning Department of Alitalia, for his support.  ...  Finally, many thanks to the anonymous referees for their helpful and constructive comments.  ...  Network Output Y Network Input Vector X Input Layer Hidden Layer Output Layer Figure 1 : A feed-forward three-layer neural network.  ... 

Abstracts of the Scientific Sessions from the WFC'S 12th Biennial Congress Proceedings, Durban, South Africa, April 10-13, 2013

2013 Journal Chiropractic Medicine  
The WFC call for abstracts resulted in 173 submissions from 14 countries (Australia, and the United States). From these abstracts, 32 platform and 85 posters were selected for presentation.  ...  Previous research exploring the neural mechanisms which underlie the shape and parameters of the input-output relation have suggested that the MEPmax, also known as the plateau of the sigmoidal shaped  ...  Extreme variable input into policy changes also indicated that the modeled data was stable and provided reasonable boundaries for model robustness.  ... 
doi:10.1016/j.jcm.2013.07.001 pmid:24294151 pmcid:PMC3730296 fatcat:4d7tr2uvpbfmhai3qjohmakvke


Politechnika Warszawska, Randall, Raj Rao, Dr Gajraj, Singh Yadava
Neural model is based on static feedforward artificial neural networks and measurements from steam 200 MW power unit. The networks give reference steam flow parameters for current operation settings.  ...  NEURAL NETWORKS IN FAULT DETECTION For the model-based approach [18, 40] , the neural network replaces the analytical model that describes the process under the normal operating conditions [15, 43] .  ...  In this paper automatic rule induction algorithms are used to knowledge acquisition from data base for marine diesel engine diagnostic expert system.  ... 

Advanced methods for product control and process monitoring

Ioan Liviu Baciu
The same procedure will be done for all the 8 tables.  ...  Attention, for saving the file as *.TXT file, we must select in "SAVE AS" window, the "TXT" options, and the name of the file will include the ". TXT".  ...  Neural Network analysis In the Figure IV .21 and IV.27, the Neural Network output is reported vs. # of input patterns for the work materials.  ... 
doi:10.6092/unina/fedoa/1467 fatcat:eil4qn7vdzhzfjejrv5e3li3jm