Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Abdul Azeez Abdul Raheem"'
Publikováno v:
Advances in Fuzzy Systems, Vol 2012 (2012)
Sensitivity-based linear learning method (SBLLM) has recently been used as a predictive tool due to its unique characteristics and performance, particularly its high stability and consistency during predictions. However, the generalisation capability
Externí odkaz:
https://doaj.org/article/b531cc592125438fb08b447d499efb3b
Publikováno v:
Applied Soft Computing. 14:144-155
This paper proposed an improved sensitivity based linear learning method (SBLLM) model through the hybridization of type-2 fuzzy logic systems (type-2 FLS) and SBLLM. The generalization abilities of the SBLLM often rely on whether the available datas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09a83d4683b2926ea03bcbd2e48ceda2
https://doi.org/10.1016/j.asoc.2013.02.018
https://doi.org/10.1016/j.asoc.2013.02.018
Publikováno v:
International Journal of Digital Content Technology and its Applications. 7:450-459
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80ee0fd1ea7fd71092b7f92660372dcd
https://doi.org/10.4156/jdcta.vol7.issue1.52
https://doi.org/10.4156/jdcta.vol7.issue1.52
Autor:
A.A. Muhammadain, S. Shujath Ali, Abdul Azeez Abdul Raheem, S. Nizamuddin, Muhammad Ali Al-Marhoun
Publikováno v:
Journal of Petroleum Science and Engineering. :111-117
Viscosity of crude oil is an important physical property that controls and influences the flow of oil through rock pores and eventually dictating oil recovery. Prediction of crude oil viscosity is one of the major challenges faced by petroleum engine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::757fd39cb975cd24c67b4bfc9f5afb26
https://doi.org/10.1016/j.petrol.2012.03.029
https://doi.org/10.1016/j.petrol.2012.03.029
Publikováno v:
Engineering Applications of Artificial Intelligence. 24:686-696
This paper presented a new prediction model of pressure-volume-temperature (PVT) properties of crude oil systems using sensitivity based linear learning method (SBLLM). PVT properties are very important in the reservoir engineering computations. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::832769bce2a6c147223279a309111b22
https://doi.org/10.1016/j.engappai.2010.10.007
https://doi.org/10.1016/j.engappai.2010.10.007
Publikováno v:
Computational Collective Intelligence. Technologies and Applications ISBN: 9783642346293
ICCCI (1)
ICCCI (1)
In this paper, we studies on a prediction model of Pressure-Volume-Temperature (PVT) properties of crude oil systems using a hybrid type-2 fuzzy logic system (type-2 FLS) and sensitivity based linear learning method (SBLLM). The PVT properties are ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b147d9996f660e32b335a733b53ca867
https://doi.org/10.1007/978-3-642-34630-9_15
https://doi.org/10.1007/978-3-642-34630-9_15
Publikováno v:
2011 Malaysian Conference in Software Engineering.
Sensitivity based linear learning method (SBLLM) has recently been used as predictive tool due to its unique characteristics and performance, particularly its high stability and consistency during predictions. However, the generalization capability o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb9c44d055559f9e50df575be1392a75
https://doi.org/10.1109/mysec.2011.6140697
https://doi.org/10.1109/mysec.2011.6140697
Publikováno v:
2010 International Conference on Multimedia Computing and Information Technology (MCIT).
This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::feb248551993e6de8cfd96d5ff7e1dcd
https://doi.org/10.1109/mcit.2010.5444846
https://doi.org/10.1109/mcit.2010.5444846
Publikováno v:
2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.
In this work, an extreme learning machine (ELM) has been used in predicting permeability from well logs data have been investigated and a prediction model has been developed. The prediction model has been constructed using industrial reservoir datase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c07e5e2ed2548dae9dc2f13e831da9e2
https://doi.org/10.1109/ams.2010.19
https://doi.org/10.1109/ams.2010.19
Publikováno v:
Computational Collective Intelligence. Technologies and Applications ISBN: 9783642166921
ICCCI (1)
ICCCI (1)
This paper presented a prediction model of Pressure-Volume-Temperature (PVT) properties of crude oil systems based on type-2 fuzzy logic systems. PVT properties are very important in the reservoir engineering computations, and its accurate determinat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2fe20eefde42c44f05a71015151f440
https://doi.org/10.1007/978-3-642-16693-8_51
https://doi.org/10.1007/978-3-642-16693-8_51