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Cooperative fault detection and isolation in a surveillance sensor network: a case study

Julien Marzat, Hélène Piet-Lahanier, Sylvain Bertrand
2018 IFAC-PapersOnLine  
A review of the main characteristics of faults in sensor networks and the associated diagnosis techniques is first proposed.  ...  This work focuses on Fault Detection and Isolation (FDI) among sensors of a surveillance network.  ...  These tasks generally involve the generation of residuals, which are fault indicators based on discrepancies between measurements and model-based computations.  ... 
doi:10.1016/j.ifacol.2018.09.665 fatcat:slpdgvckrvhxxljvsmcjnazi4i

Multi-disciplinary analysis and optimization under uncertainty [chapter]

C Liang, S Mahadevan
2014 Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures  
selectively based on the sculpting strategy.  ...  To evaluate this method, Latin Hypercube sampling (LHS) is also used to generate 20 samples of the design variables from uniform distributions based onTables 1 and 2, and propagated to estimate the outputs  ...  A vine copula-based strategy is therefore adopted to efficiently generate conditional samples.  ... 
doi:10.1201/b16387-415 fatcat:2u3vrd4orjavroggn7tqb6f3uq

Artificial Intelligence in Civil Engineering

Pengzhen Lu, Shengyong Chen, Yujun Zheng
2012 Mathematical Problems in Engineering  
Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives  ...  The paper provides an overview of the advances of artificial intelligence applied in civil engineering.  ...  On the test problem, solutions are represented by electric wires and are evaluated on two levels: a global level, using the objective function, and a local level, evaluating the potential of each generated  ... 
doi:10.1155/2012/145974 fatcat:asd3grpoabf5xn6tdpctxkxtwy

ICONE19-43254 TOWARDS A BETTER UNDERSTANDING OF CLOGGED STEAM GENERATORS : A SENSITIVITY ANALYSIS OF DYNAMIC THERMOHYDRAULIC MODEL OUTPUT

Sylvain Girard, Thomas Romary, Jean-Melaine Favennec, Pascal Stabat, Hans Wackernagel
2011 The Proceedings of the International Conference on Nuclear Engineering (ICONE)  
A diagnosis method based on dynamic behaviour analysis is under development at EDF to provide means of optimisation of maintenance strategies.  ...  The diagnosis method consists of comparisons of the measured dynamic response with simulations on a mono-dimensional dynamic steam generator model for various input clogging configurations.  ...  A diagnosis method based on the comparison of plant WRL response with simulated responses is being developed by EDF.  ... 
doi:10.1299/jsmeicone.2011.19._icone1943_106 fatcat:ika6bdoxqzdx7hhvjsxi35empe

Probabilistic Risk Assessment [chapter]

William E. Vesely
2011 System Health Management  
The models are based on continuous time Markov processes, and are a generalization of reliability models currently used in Probabilistic Risk Assessment.  ...  MagnoxElectric has devised and implemented a strategy to manage the threat from SCC, based on a probabilistic risk assessmenttechnique.  ...  The impact of the core damage progression and lower plenum quenching models on the likelihood of terminating the damage progression in-vessel was evaluated.  ... 
doi:10.1002/9781119994053.ch15 fatcat:ngp7pbndpvbunpxo4v6sh24iaa

Catchment scale hydrological modelling: A review of model types, calibration approaches and uncertainty analysis methods in the context of recent developments in technology and applications

2013 Global NEST Journal  
We summarise different methods to quantify uncertainty in the model predictions that could sit well within a model evaluation framework.  ...  In this review, we summarise the different classifications of hydrological model types, and discuss relative advantages and disadvantages of each type of model.  ...  A powerful extension of sensitivity analysis is to evaluate the dynamic sensitivity of model parameters, for example by evaluating sensitivity based on a moving window passed through the observed and simulated  ... 
doi:10.30955/gnj.000778 fatcat:smzexxlaezd6xktkeau3lcxusm

A sequential distance-based approach for imputing missing data: Forward Imputation

Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari
2016 Advances in Data Analysis and Classification  
exchange rate pairs are evaluated and compared.  ...  Sets of regression functions can be obtained from regression methods that are based on imprecise probability models, like the recently introduced Likelihood-based Imprecise Regression, but they can also  ... 
doi:10.1007/s11634-016-0243-0 fatcat:yvrqlgllsbesbnvnzzci2egpl4

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

Cisternas, Lucay, Botero
2019 Minerals  
New strategies for the modeling, design, and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation  ...  The paper finishes with tools to study the uncertainty, both epistemic and stochastic, based on uncertainty and global sensitivity analyses, which is present in all mineral processing operations.  ...  Thanks the supported of MINEDUCUA project, code ANT1856. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/min10010022 fatcat:tnsybjbitbbh3jtnyo4w3r45sa

Bioinformatics with soft computing

S. Mitra, Y. Hayashi
2006 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
RSes for modeling ambiguity, searching potential of genetic algorithms for efficiently traversing large search spaces, and the generalization capability of SVMs for minimizing errors.  ...  The major pattern-recognition and data-mining tasks considered here are clustering, classification, feature selection, and rule generation.  ...  to achieve reliable and accurate classification based on their expression levels.  ... 
doi:10.1109/tsmcc.2006.879384 fatcat:owim7m6genf6xc7s2bbhjuz7gu

The use of computational intelligence in intrusion detection systems: A review

Shelly Xiaonan Wu, Wolfgang Banzhaf
2010 Applied Soft Computing  
The scope of this review will be on core methods of CI, including artificial neural networks, fuzzy systems, evolutionary computation, artificial immune systems, swarm intelligence, and soft computing.  ...  Intrusion detection based upon computational intelligence is currently attracting considerable interest from the research community.  ...  Commonly employed methods are generating rules based on the histogram of attribute values [10, 11] , or based on partition of overlapping areas [10, 11, 184] , or based on fuzzy implication tables [  ... 
doi:10.1016/j.asoc.2009.06.019 fatcat:5ntbfbejrveyzhmmelfh34qkiy

Historical Relationship Between Performance Assessment for Radioactive Waste Disposal and Other Types of Risk Assessment

Rob P. Rechard
1999 Risk Analysis  
The evaluation of risk to human health and the environment from chemical hazards is built on methods for assessing the dose response of radionuclides in the 1950s.  ...  Computational tools and techniques developed in the late 1950s and early 1960s to analyze the reliability of nuclear weapon delivery systems were adopted in the early 1970s for probabilistic risk assessment  ...  Furthermore, the focus of many assessments is on only one of the general steps (i.e., evaluating the dose response of a receptor to a chemical agent).  ... 
doi:10.1111/j.1539-6924.1999.tb00446.x pmid:10765434 fatcat:ommpqo565beqvfs5uaypmkijoe

EI2 2019 Final Program

2019 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2)  
➤ PoB-15 A Novel Reliability Assessment Method of Microgrid Based on Time Correlation Model Pude Li Hunan Institute of Engineering Ming Li Hunan University ➤ PoB-17 Reliability Analysis  ...  Probabilistic Load Flow Calculation Method Based on Polynomial Normal Transformation and Extended Latin hypercube Wei Chen Lanzhou Univ. of Tech. Xiaoyan Li Lanzhou Univ. of Tech.  ... 
doi:10.1109/ei247390.2019.9062229 fatcat:tklkkegnqfannl2bxskhrdegmi

Engineering, Technology & Applied Science Research (ETASR), Vol. 11, No. 2, pp. 6845-7068 [article]

Various
2021 Zenodo  
of science application, technology, and engineering.  ...  ETASR is indexed in the Web of Science Core Collection (former Web of Science/Thomson Reuters Master Journal List), through the Emerging Sources Citation Index, is a Crossref member (DOI prefix: 10.48084  ...  ACKNOWLEDGEMENT The authors express our sincere thanks to the General Directorate of Scientific Research and Technological Development (DGRSDT) for their support in the development of this work.  ... 
doi:10.5281/zenodo.4720665 fatcat:mk2prflstjaa3bhkjenwy22s6u

Application of Computational Intelligence to Energy Systems

Matteo De Felice
2011 Zenodo  
Moreover this work raises the issue of reducing the computational load of stochastic algorithms such the ones we used of real problems, where the evaluation of a solution is based on the execution of a  ...  model, based on NN, has been used for the GA, which commonly requires an elevate number of fitness evaluations (in this case CFD simulations).  ...  Appendix A Computational Intelligence in Software Packages This appendix gives a list of some of the most common software implementations of neural networks and computational intelligence algorithms.  ... 
doi:10.5281/zenodo.4068383 fatcat:ee6uyhkcdzh3hlvty33twlqnva

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
The TriRhenaTech alliance presents the accepted papers of the 'Upper-Rhine Artificial Intelligence Symposium' held on October 27th 2021 in Kaiserslautern, Germany.  ...  The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe  ...  This work was funded by the Ministry of Science, Research and Arts of Baden-Württemberg (MWK) as part of the project Q-AMeLiA (Quality Assurance of Machine Learning Applications).  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni
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