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Software Reliability Assesment using Neural Networks of Computational Intelligence Based on Software Failure Data

Manmath Kumar Bhuyan, Durga Prasad Mohapatra, Srinivas Sethi
2016 Baltic Journal of Modern Computing  
The computational intelligence approach using Neural Network (NN) has been known to be very useful in predicting software reliability. Software reliability plays a key role in software quality.  ...  In order to improve accuracy and consistency of software reliability prediction, we propose the applicability of Feed Forward Back-Propagation Network (FFBPN) as a model to predict software reliability  ...  Our propose model's prediction is based on failure data collected in the process of software system testing or operation.  ... 
doi:10.22364/bjmc.2016.4.4.26 fatcat:f2lhi4a4nbgslebugaw63bdanu

A Framework for Intelligent Condition-based Maintenance of Rotating Equipment using Mechanical Condition Monitoring

Mohammadreza Tahan B., Masdi Muhammad, Z. A. Abdul Karim, S. Karuppanan, Z. A. Abdul Karim, M. Ovinis, A. Tesfamichael Baheta
2014 MATEC Web of Conferences  
In order to standardize a generic architecture for machinery CBM, this paper attempts to introduce an intelligent framework consisting of several functional modules, starting from data acquisition and  ...  In condition-based maintenance (CBM), asset health is monitored regularly to maximize reliability and availability by determining necessary maintenance at the right time.  ...  Scheduled at regular time intervals based on failure history or test data Manual data collection Prevent the functional failures by replacing critical components Equipment may be overhauled when  ... 
doi:10.1051/matecconf/20141305011 fatcat:ji627bunrzc3rf7ekjd4w33m74

Preventing large-scale blackouts in power systems under uncertainty

Michael Negnevitsky, Nikita Tomin, Daniil Panasetsky, Nikolai Voropai, Victor Kurbatsky, Ulf Hager, Christian Rehtanz
2014 2014 Power Systems Computation Conference  
In this paper, an intelligent viable approach is proposed to minimize the threat of large-scale blackouts under uncertainty.  ...  The developed system was tested on the modified IEEE One Area RTS-96 power system.  ...  We examined a clustering approach based on the self-organized Kohonen neural network.  ... 
doi:10.1109/pscc.2014.7038340 dblp:conf/pscc/NegnevitskyTPVK14 fatcat:2glcnunapvbwvety2tew5owd4m


2020 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA)  
' Failures Time During the Proactive Maintenance Using the Recurrent Neural Networks' Technology Irina Sedykh and Vladimir Istomin 375 Management of the Strip Cooling Process Using Neural Networks Based  ...  Indicators in the Context of Sustainable Development Dmitriy Kovtun, Matvey Koptelov and Anna Guseva 228 Megaproject Risk Management Based on Loyalty Program Using Neural Network Models Support in Ill-defined  ... 
doi:10.1109/summa50634.2020.9280691 fatcat:7kmyfu5varfsvoic3bdz4nyxae

Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study

Fernando Castaño, Stanisław Strzelczak, Alberto Villalonga, Rodolfo E. Haber, Joanna Kossakowska
2019 Remote Sensing  
The results demonstrate the effectiveness of the proposed method for increasing sensor reliability in cyber-physical systems using Internet-of-Things data.  ...  Nowadays, reliability of sensors is one of the most important challenges for widespread application of Internet-of-things data in key emerging fields such as the automotive and manufacturing sectors.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11192252 fatcat:7q5kuvx6yjezpolh5reuhcssri

Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments

Jorge Luis Reyes-Ortiz, Alessandro Ghio, Xavier Parra, Davide Anguita, Joan Cabestany, Andreu Català
2013 The European Symposium on Artificial Neural Networks  
The rise of ubiquitous computing systems in our environment is engendering a strong need for novel approaches of human-computer interaction.  ...  recently published data set.  ...  They achieved an accuracy of 94.33% on the test set. 409 ESANN 2013 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.  ... 
dblp:conf/esann/Reyes-OrtizGPACC13 fatcat:537ouyuhgfhg5oufzpmhuxsvwy

Development of a prognostics and health management system for the railway infrastructure — Review and methodology

M. Brahimi, K. Medjaher, M. Leouatni, N. Zerhouni
2016 2016 Prognostics and System Health Management Conference (PHM-Chengdu)  
These models are based on two overlapping domain [13] : the Computational Intelligence (CI) models such as fuzzy logic and neural networks; the Machine Learning (ML) models such us support vector machines  ...  In [3] a methodology based on FMEA analysis is proposed to determine criticality of OCS system based on failure records for decision-making.  ... 
doi:10.1109/phm.2016.7819783 fatcat:ljaktk4flnanzeixx4wh2jpuy4

Priorities assignment for actions in a transport system based on a multicriteria decision model [chapter]

2009 Reliability, Risk, and Safety, Three Volume Set  
"Some characteristics of one type of high reliability in organisation." Organisation Science, 1 (2), 160-176. Rundmo T. 1997.  ...  Wreathall, J. 2007 "The use of Performance Indicators in Resilient Risk Management" in Workshop on Resilient Risk Management Juan-les-Pines 2007.  ...  Mechanical Systems and Signal Processing, 22 (1) (2007) Intelligent condition monitoring of a gearbox using arti?cial neural network.  ... 
doi:10.1201/9780203859759-69 fatcat:wnkjp4evmnawrn55cmckrgazze

The cloudUPDRS app: A medical device for the clinical assessment of Parkinson's Disease

C. Stamate, G.D. Magoulas, S. Kueppers, E. Nomikou, I. Daskalopoulos, A. Jha, J.S. Pons, J. Rothwell, M.U. Luchini, T. Moussouri, M. Iannone, G. Roussos
2018 Pervasive and Mobile Computing  
To address the former, we combine a bespoke design of the user experience tailored so as to constrain context, with a deep learning approach based on Recurrent Convolutional Neural Networks, to identify  ...  failures  ...  process the data using specialist software.  ... 
doi:10.1016/j.pmcj.2017.12.005 fatcat:zmoucmxpsjcr5mjvcnidiqpphq

Data analytics to reduce stop-on-fail test in electronics manufacturing

Ana Elsa Hinojosa Herrera, Stoyan Stoyanov, Chris Bailey, Chris Walshaw, Chunyan Yin
2019 Open Computer Science  
The use of data driven techniques is popular in smart manufacturing. Machine learning, statistics or a combination of both have been used to improve processes in electronic manufacturing.  ...  Data generated in the production test-set on stop-on-fail scenario challenges the traditional application of the data driven techniques, because of the missing data characteristic.  ...  Marc Cavazza (Head of the School of Computing and Mathematical Sciences at the University of Greenwich) for his valuable and constructive suggestions during the planning and development of this research  ... 
doi:10.1515/comp-2019-0014 fatcat:e2h47a2gxncmbotq7gi3wife3q

Systematic literature review of validation methods for AI systems

Lalli Myllyaho, Mikko Raatikainen, Tomi Männistö, Tommi Mikkonen, Jukka K. Nurminen
2021 Journal of Systems and Software  
Systems presented in the papers were analysed based on their domain, task, complexity, and applied validation methods.  ...  Failure monitors, safety channels, redundancy, voting, and input and output restrictions are methods used to continuously validate the systems after deployment.  ...  As data-driven ML testing in general, a large part of the validations based on model-centred approaches are prone to data problems .  ... 
doi:10.1016/j.jss.2021.111050 fatcat:ijfgxvnrjvef3fzdak34mdzpai

Acceptance in incomplete argumentation frameworks

Dorothea Baumeister, Matti Järvisalo, Daniel Neugebauer, Andreas Niskanen, Jörg Rothe
2021 Artificial Intelligence  
Systems presented in the papers were analysed based on their domain, task, complexity, and applied validation methods.  ...  Failure monitors, safety channels, redundancy, voting, and input and output restrictions are methods used to continuously validate the systems after deployment.  ...  As data-driven ML testing in general, a large part of the validations based on model-centred approaches are prone to data problems .  ... 
doi:10.1016/j.artint.2021.103470 fatcat:cmf2rikpaja5zdboq5zp6zr46y

Abnormality Detection and Failure Prediction Using Explainable Bayesian Deep Learning: Methodology and Case Study with Industrial Data

Ahmad Kamal Mohd Nor, Srinivasa Rao Pedapati, Masdi Muhammad, Víctor Leiva
2022 Mathematics  
The elaborated framework is tested on real-world gas turbine anomalies and synthetic turbofan failure prediction data. Seven out of eight of the tested anomalies were successfully identified.  ...  In addition, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of studies on PHM-XAI.  ...  Acknowledgments: The authors would like to thank Petronas Bhd. for the data used in this work.  ... 
doi:10.3390/math10040554 fatcat:2o74pihvgzat3madj7jwal7iha

Advances in Distributed Computing and Artificial Intelligence Jornual, 2013, vol. 1, n. 4, pp. 1-66

Ediciones Universidad de Salamanca
2013 Advances in Distributed Computing and Artificial Intelligence Journal  
Finally, the Editors wish to thank Scientific Committee of Advances in Distributed Computing and Artificial Intelligence Journal for the collaboration of this special issue, that notably contributes to  ...  SCOPE The Advances in Distributed Computing and Artificial Intelligence Journal (ADCAIJ) is an open access journal that publishes articles which contribute new results associated with distributed computing  ...  In Ambient Intelligence -Software and Applications, volume 92 of Advantages in Intelligent and Soft Computing, Springer, 2011, Berlin / Heidelberg, pp. 189-196.  ... 
doaj:5945a03d7dab4b20be1b3dbd6fef9c7c fatcat:eyn3fum7eja5zp3uugateci4km

Green IoT: An Investigation on Energy Saving Practices for 2020 and Beyond

Rushan Arshad, Saman Zahoor, Munam Ali Shah, Abdul Wahid, Hongnian Yu
2017 IEEE Access  
We then discuss and evaluate the strategies that can be used to minimize the energy consumption in IoT, such as designing energy efficient datacenters, energy efficient transmission of data from sensors  ...  INDEX TERMS Internet of things, green IoT, datacenter, green computing, smart phones.  ...  , healthcare, transportation networks, computer networks and RFID applications, modeling and control of robots and mechatronics, and neural networks.  ... 
doi:10.1109/access.2017.2686092 fatcat:n6ofdpgfkvbobos7wjrj63tqxa
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