Výsledky vyhledávání - "Cesar A. Penz"

Akademický článek

Use of self organizing map to identify precipitation patterns and assess their impact on hydrographic basins in Brazil

Autor: Yoshiaki Sakagami, Vinicius Nunes Folganes, Cesar Alberto Penz, Murilo Reolon Scuzziato, Fabrício Yutaka Kuwabata Takigawa

Publikováno v: Revista Brasileira de Recursos Hídricos, Vol 27 (2022)

ABSTRACT In this study, we used neural networks known as self-organizing maps (SOMs) to identify clusters of spatial synoptic precipitation patterns. These clusters were compared with the precipitation regime of the ten main hydrographic sub-basins i

Externí odkaz: https://doaj.org/article/353e562ec7cd4eb990019547c5fe49b5

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Diagnosis of rotating machine unbalance using machine learning algorithms on vibration orbital features

Autor: Fabrizio Leal Freitas, Cesar A. Penz, Leonardo S Jablon, S.L. Avila, Gustavo L Mourão, Bruno de Borba

Publikováno v: Journal of Vibration and Control. 27:468-476

The diagnosis of failures in rotating machines has been subject to studies because of its benefits to maintenance improvement. Condition monitoring reduces maintenance costs, increases reliability and availability, and extends the useful life of crit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::947e5cf45d49b73ed489370771f85d7b
https://doi.org/10.1177/1077546320929830

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Measurement of the friction forces between piston and cylinder in reciprocating machines using the connecting rod strain behavior

Autor: Cesar A. Penz, Leonardo do Nascimento Cervelin, Rodolfo C.C. Flesch, Julio Nelson Scussel, Carlos Alberto Flesch

Publikováno v: Mechanical Systems and Signal Processing. 130:677-691

The design of slider-crank mechanisms is usually done using numerical simulation supported by experiments to validate the results of both the individual parts and whole assembly. The largest challenge in this process is to establish parameters to eva

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::454aef9623c9c1d829c000f2e522eda0
https://doi.org/10.1016/j.ymssp.2019.05.026

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A Monte Carlo-Based Method for Assessing the Measurement Uncertainty in the Training and Use of Artificial Neural Networks

Autor: Carlos Alberto Flesch, Mauro Roisenberg, Rodrigo Coral, Antonio Luiz Schalata Pacheco, Cesar A. Penz

Publikováno v: Metrology and Measurement Systems, Vol 23, Iss 2, Pp 281-294 (2016)

When an artificial neural network is used to determine the value of a physical quantity its result is usually presented without an uncertainty. This is due to the difficulty in determining the uncertainties related to the neural model. However, the r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28e9ff06e3ea9fd59887615822bc4918
https://doi.org/10.1515/mms-2016-0015

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Development of a Committee of Artificial Neural Networks for the Performance Testing of Compressors for Thermal Machines in Very Reduced Times

Autor: Carlos Alberto Flesch, Maikon R. Borges, Rodrigo Coral, Cesar A. Penz

Publikováno v: Metrology and Measurement Systems, Vol 22, Iss 1, Pp 79-88 (2015)

This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized tradi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7eaae6411ac73b4ae5dcf9d6607225a
https://doi.org/10.1515/mms-2015-0003

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Fuzzy–Bayesian network for refrigeration compressor performance prediction and test time reduction

Autor: Rodolfo C.C. Flesch, Cesar A. Penz, Marco Aurélio de Oliveira, Carlos Alberto Flesch, Silvia Modesto Nassar

Publikováno v: Expert Systems with Applications. 39:4268-4273

A typical characteristic of refrigeration compressor performance tests is their long duration. A reduction in the time periods related to this activity can be achieved using unsteady-state data analysis. This paper presents an original approach to pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::725ff5f9c24680442849f9784d5de362
https://doi.org/10.1016/j.eswa.2011.09.107

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Steady-State Inference in Performance Tests of Refrigeration Compressors Using ANN Ensemble

Autor: Cesar A. Penz, João Paulo Rossetto, Carlos Alberto Flesch

Publikováno v: IFIP Advances in Information and Communication Technology ISBN: 9783319238678
AIAI

The use of ensembles is an important way to ensure reliability of ANN-based tools. This article presents the development of an ANNs ensemble to infer steady-state in performance tests related to refrigeration compressors. Practical results are presen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bd4421375d3e93f52813a9780ac0c6e7
https://doi.org/10.1007/978-3-319-23868-5_26

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