Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Fouad Bahrpeyma"'
Autor:
Fouad Bahrpeyma, Dirk Reichelt
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
The smart factory is at the heart of Industry 4.0 and is the new paradigm for establishing advanced manufacturing systems and realizing modern manufacturing objectives such as mass customization, automation, efficiency, and self-organization all at o
Externí odkaz:
https://doaj.org/article/a1e68bcd90f74fc3be941f5dbb0dd709
Publikováno v:
MethodsX, Vol 8, Iss , Pp 101459- (2021)
In order for researchers to deliver robust evaluations of time series models, it often requires high volumes of data to ensure the appropriate level of rigor in testing. However, for many researchers, the lack of time series presents a barrier to a d
Externí odkaz:
https://doaj.org/article/677b2700240a4604bb195288aade4b10
Publikováno v:
Logistics, Vol 6, Iss 2, p 35 (2022)
Background: Today’s production facilities must be efficient in both manufacturing and maintenance. Efficiency enables the company to maintain the required output while reducing production effort or costs. With the increasing interest in process aut
Externí odkaz:
https://doaj.org/article/a3325e171b354c458df47518926a3a10
Publikováno v:
MethodsX
MethodsX, Vol 8, Iss, Pp 101459-(2021)
Bahrpeyma, Fouad ORCID: 0000-0002-5128-4774, Roantree, Mark ORCID: 0000-0002-1329-2570 , Cappellari, Paolo, Scriney, Michael ORCID: 0000-0001-6813-2630 and McCarren, Andrew ORCID: 0000-0002-7297-0984 (2021) A methodology for validating diversity in synthetic time series generation. MethodsX . ISSN 2215-0161
MethodsX, Vol 8, Iss, Pp 101459-(2021)
Bahrpeyma, Fouad ORCID: 0000-0002-5128-4774
Highlights • This paper presents a new method for generating 50K diverse synthetic time series. • We present a discussion on time series characteristics and metrics with a view to understanding time series diversity. • We developed a robust fra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f87ed3e8f372343352e8c999d9af9e5
http://europepmc.org/articles/PMC8374706
http://europepmc.org/articles/PMC8374706
Publikováno v:
Neural Computing and Applications. 27:1981-1992
While active learning method (ALM) uses error as the learning parameter, selection of the validation data is still challenging. In this paper, to prevent form encountering with sample size problem, we applied an error-independent version of ALM that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09412a46f221cf11d19cca5bdd0b4032
https://doi.org/10.1007/s00521-015-1992-y
https://doi.org/10.1007/s00521-015-1992-y
Publikováno v:
Computing. 97:1209-1234
Because of numerous parameters existing in the Cloud's environment, it is helpful to introduce a general solution for dynamic resource provisioning in Cloud that is able to handle uncertainty. In this paper, a novel adaptive control approach is propo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba0eb29a4d53d98af6f8ea42b2ea7664
https://doi.org/10.1007/s00607-015-0455-8
https://doi.org/10.1007/s00607-015-0455-8
Publikováno v:
Applied Soft Computing. 26:285-298
RL based adaptive control via IDSFQ for dynamic resource provisioning in Cloud's virtualized environment. In this paper, a fast fuzzy solution is proposed to enable application of reinforcement learning in continuous domains of state-action pairs.In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea351814d0fba7f644ac2e3f0164c872
https://doi.org/10.1016/j.asoc.2014.10.005
https://doi.org/10.1016/j.asoc.2014.10.005
Publikováno v:
Journal of Petroleum Science and Engineering. 112:310-321
In order to deal with huge amounts of computational complexities, conventional modeling systems always had to choose a tradeoff between accuracy and rapidity and usually one prevails over the other. Thus there is a need for a solution which provides
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6734fe59c5a685edcae4b6718b13a6f8
https://doi.org/10.1016/j.petrol.2013.11.019
https://doi.org/10.1016/j.petrol.2013.11.019
Publikováno v:
Artificial Intelligent Approaches in Petroleum Geosciences ISBN: 9783319165301
Characterization and estimation of physical properties are two of the most important key activities for successful exploration and exploitation in the petroleum industry. Pore-fluid pressures as well as estimating permeability, porosity, or fluid sat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a0b13d81d567b13b77e51c9c63404f8
https://doi.org/10.1007/978-3-319-16531-8_7
https://doi.org/10.1007/978-3-319-16531-8_7
Autor:
Fouad Bahrpeyma, Constantin Cranganu
Publikováno v:
Artificial Intelligent Approaches in Petroleum Geosciences ISBN: 9783319165301
We discuss active learning method (ALM) as an artificial intelligent approach for predicting a missing log (DT or sonic log) when only two other logs (GR and REID) are present. Applying ALM approach involves three steps: (1) supervised training of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eda27719b2beb9eec7ebf46c531b59e
https://doi.org/10.1007/978-3-319-16531-8_6
https://doi.org/10.1007/978-3-319-16531-8_6