Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography.
Recognition of gas-liquid flow regimes in pipelines is important in an industrial control process such as for oil production. In oil production, gas-liquid flows are normally concealed in a pipe the actual type of flows cannot be easily determined. Also, obtaining measurements corresponding to the...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://eprints.usm.my/8612/ http://eprints.usm.my/8612/1/Neural_Computation_for_Flow_Regime_Classification_Based_on_Electrical_%28PPKEElektronik%29_2004.pdf |
| _version_ | 1848870530490302464 |
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| author | Mat-Dan, A. A. Mohamad-Saleh, J Ahmad, M. A. |
| author_facet | Mat-Dan, A. A. Mohamad-Saleh, J Ahmad, M. A. |
| author_sort | Mat-Dan, A. A. |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Recognition of gas-liquid flow regimes in pipelines is important in an industrial control process such as for oil production. In oil production, gas-liquid flows are normally concealed in a pipe the actual type of flows cannot be easily determined. Also, obtaining measurements corresponding to the flow distribution becomes almost impossible. |
| first_indexed | 2025-11-15T15:25:39Z |
| format | Conference or Workshop Item |
| id | usm-8612 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T15:25:39Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-86122017-11-20T07:22:10Z http://eprints.usm.my/8612/ Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. Mat-Dan, A. A. Mohamad-Saleh, J Ahmad, M. A. TK1-9971 Electrical engineering. Electronics. Nuclear engineering Recognition of gas-liquid flow regimes in pipelines is important in an industrial control process such as for oil production. In oil production, gas-liquid flows are normally concealed in a pipe the actual type of flows cannot be easily determined. Also, obtaining measurements corresponding to the flow distribution becomes almost impossible. 2004 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/8612/1/Neural_Computation_for_Flow_Regime_Classification_Based_on_Electrical_%28PPKEElektronik%29_2004.pdf Mat-Dan, A. A. and Mohamad-Saleh, J and Ahmad, M. A. (2004) Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. In: 1st National Postgraduate Colloquium School of Chemical Engineering, USM, 2004, School of Chemical Engineering, USM. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Mat-Dan, A. A. Mohamad-Saleh, J Ahmad, M. A. Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title | Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title_full | Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title_fullStr | Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title_full_unstemmed | Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title_short | Neural Computation For Flow Regime Classification Based On Electrical Capacitance Tomography. |
| title_sort | neural computation for flow regime classification based on electrical capacitance tomography. |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/8612/ http://eprints.usm.my/8612/1/Neural_Computation_for_Flow_Regime_Classification_Based_on_Electrical_%28PPKEElektronik%29_2004.pdf |