Search Results - "Amar, Menad Nait"

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  1. 1

    Evolving support vector regression using Grey Wolf optimization; forecasting the geomechanical properties of rock by Xu, Chuanhua, Nait Amar, Menad, Ghriga, Mohammed Abdelfetah, Ouaer, Hocine, Zhang, Xiliang, Hasanipanah, Mahdi

    Published in Engineering with computers (01-04-2022)
    “…The geomechanical properties of rock, including shear strength (SS) and uniaxial compressive strength (UCS), are very important parameters in designing rock…”
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    Journal Article
  2. 2

    Optimization of WAG Process Using Dynamic Proxy, Genetic Algorithm and Ant Colony Optimization by Nait Amar, Menad, Zeraibi, Nourddine, Redouane, Kheireddine

    “…The optimization of water alternating gas injection (WAG) process is a complex problem, which requires a significant number of numerical simulations that are…”
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  3. 3

    On the evaluation of the carbon dioxide solubility in polymers using gene expression programming by Amiri-Ramsheh, Behnam, Nait Amar, Menad, Shateri, Mohammadhadi, Hemmati-Sarapardeh, Abdolhossein

    Published in Scientific reports (02-08-2023)
    “…Evaluation, prediction, and measurement of carbon dioxide (CO 2 ) solubility in different polymers are crucial for engineers in various chemical applications,…”
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  4. 4

    Proxy Model Development for the Optimization of Water Alternating CO2 Gas for Enhanced Oil Recovery by Matthew, D Aqnan Marusaha, Jahanbani Ghahfarokhi, Ashkan, Ng, Cuthbert Shang Wui, Nait Amar, Menad

    Published in Energies (Basel) (01-04-2023)
    “…Optimization studies are an important task in reservoir engineering practices such as production optimization and EOR (Enhanced Oil Recovery) assessments…”
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  5. 5

    Production optimization under waterflooding with long short-term memory and metaheuristic algorithm by Cuthbert Shang Wui Ng, Ashkan Jahanbani Ghahfarokhi, Menad Nait Amar

    Published in Petroleum (01-03-2023)
    “…In petroleum domain, optimizing hydrocarbon production is essential because it does not only ensure the economic prospects of the petroleum companies, but also…”
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  6. 6

    Prediction of Wax Appearance Temperature Using Artificial Intelligent Techniques by Benamara, Chahrazed, Gharbi, Kheira, Nait Amar, Menad, Hamada, Boudjema

    “…The paraffin particles can promote and be involved in the formation of deposits which can lead to plugging of oil production facilities. In this work, an…”
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  7. 7

    Modeling solubility of sulfur in pure hydrogen sulfide and sour gas mixtures using rigorous machine learning methods by Nait Amar, Menad

    Published in International journal of hydrogen energy (27-11-2020)
    “…Accurate determination of sulfur solubility in pure hydrogen sulfide (H2S) and sour gas mixtures has a leading role and a fundamental importance in handling…”
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  8. 8

    On the evaluation of the interfacial tension of immiscible binary systems of methane, carbon dioxide, and nitrogen-alkanes using robust data-driven approaches by Mahdaviara, Mehdi, Nait Amar, Menad, Ostadhassan, Mehdi, Hemmati-Sarapardeh, Abdolhossein

    Published in Alexandria engineering journal (01-12-2022)
    “…Gas injection has emerged over the recent decades as a promising technology to enhance oil recovery in various fields worldwide. The efficiency and success of…”
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  9. 9

    Toward robust models for predicting carbon dioxide absorption by nanofluids by Nait Amar, Menad, Djema, Hakim, Belhaouari, Samir Brahim, Zeraibi, Noureddine

    Published in Greenhouse gases: science and technology (01-08-2022)
    “…The application of nanofluids has received increased attention across a number of disciplines in recent years. Carbon dioxide (CO2) absorption by using…”
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  10. 10

    Predicting wax deposition using robust machine learning techniques by Menad Nait Amar, Ashkan Jahanbani Ghahfarokhi, Cuthbert Shang Wui Ng

    Published in Petroleum (01-06-2022)
    “…Accurate prediction of wax deposition is of vital interest in digitalized systems to avoid many issues that interrupt the flow assurance during production of…”
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  11. 11

    Rigorous Connectionist Models to Predict Carbon Dioxide Solubility in Various Ionic Liquids by Ouaer, Hocine, Hosseini, Amir Hossein, Nait Amar, Menad, El Amine Ben Seghier, Mohamed, Ghriga, Mohammed Abdelfetah, Nabipour, Narjes, Andersen, Pål Østebø, Mosavi, Amir, Shamshirband, Shahaboddin

    Published in Applied sciences (01-01-2020)
    “…Estimating the solubility of carbon dioxide in ionic liquids, using reliable models, is of paramount importance from both environmental and economic points of…”
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  12. 12

    Towards improved genetic programming based-correlations for predicting the interfacial tension of the systems pure/impure CO2-brine by Nait Amar, Menad

    “…•The interfacial tension of the systems pure/impure CO2-brine was modeled using GP.•2346 authenticated points were utilized for establishing the…”
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  13. 13

    Modeling interfacial tension of the hydrogen-brine system using robust machine learning techniques: Implication for underground hydrogen storage by Ng, Cuthbert Shang Wui, Djema, Hakim, Nait Amar, Menad, Jahanbani Ghahfarokhi, Ashkan

    Published in International journal of hydrogen energy (01-12-2022)
    “…During the last years, there has been a surge of interest in cleaner ways for producing energy in order to successfully handle the climate issues caused by the…”
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  14. 14

    Robust smart schemes for modeling carbon dioxide uptake in metal − organic frameworks by Nait Amar, Menad, Ouaer, Hocine, Abdelfetah Ghriga, Mohammed

    Published in Fuel (Guildford) (01-03-2022)
    “…•CO2 uptake in MOFs was modeled using MLP-LMA, MLP-BR, ELM, and GP.•The proposed models demonstrated accurate prediction performance.•The MLP-LMA outperformed…”
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  15. 15

    Modeling wax disappearance temperature using robust white-box machine learning by Nait Amar, Menad, Zeraibi, Noureddine, Benamara, Chahrazed, Djema, Hakim, Saifi, Redha, Gareche, Mourad

    Published in Fuel (Guildford) (15-11-2024)
    “…•The WDT was modeled using a robust explicit-based ML approach.•The suggested smart correlations achieved remarkable performance.•The proposed new correlations…”
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  16. 16

    Toward smart schemes for modeling CO2 solubility in crude oil: Application to carbon dioxide enhanced oil recovery by Mahdaviara, Mehdi, Nait Amar, Menad, Hemmati-Sarapardeh, Abdolhossein, Dai, Zhenxue, Zhang, Changsong, Xiao, Ting, Zhang, Xiaoying

    Published in Fuel (Guildford) (01-02-2021)
    “…This paper presents an artificial intelligence-based numerical investigation on the CO2 solubility in live and dead oils for possible CO2-enhanced oil recovery…”
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  17. 17

    Adaptive surrogate modeling with evolutionary algorithm for well placement optimization in fractured reservoirs by Redouane, Kheireddine, Zeraibi, Noureddine, Nait Amar, Menad

    Published in Applied soft computing (01-07-2019)
    “…Well placement optimization is a decisive task for the reliable design of field development plans. The use of optimization routines coupled to reservoir…”
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  18. 18

    Application of machine learning methods for estimating and comparing the sulfur dioxide absorption capacity of a variety of deep eutectic solvents by Zhu, Xiaolei, Khosravi, Marzieh, Vaferi, Behzad, Nait Amar, Menad, Ghriga, Mohammed Abdelfetah, Mohammed, Adil Hussein

    Published in Journal of cleaner production (20-08-2022)
    “…Sulfur dioxide (SO2) is one of the main atmospheric pollutants and an active threat to human health. SO2 separation from industrial flue gases improves air…”
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  19. 19

    Modeling Wax Disappearance Temperature Using Advanced Intelligent Frameworks by Benamara, Chahrazed, Nait Amar, Menad, Gharbi, Kheira, Hamada, Boudjema

    Published in Energy & fuels (21-11-2019)
    “…The deposition of wax is one of the most potential problems that disturbs the flow assurance during production processes of hydrocarbon fluids. In this study,…”
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  20. 20

    On the evaluation of solubility of hydrogen sulfide in ionic liquids using advanced committee machine intelligent systems by Nait Amar, Menad, Ghriga, Mohammed Abdelfetah, Ouaer, Hocine

    “…Ionic Liquids (ILs) are increasingly emerging as new innovating green solvents with great importance from academic, industrial, and environmental perspectives…”
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