Výsledky vyhledávání - "Gholam, Khayati"

Akademický článek

Biodegradation of Nicotine Using Aerobic Granules in Sequence Batch Reactor

Autor: Mohadeseh Shahriari, Gholam Khayati

Publikováno v: آب و فاضلاب, Vol 35, Iss 2, Pp 40-52 (2024)

Nicotine is a substance widely consumed globally as a drug. Due to its toxic nature and high solubility in water, it poses a significant threat to water quality. This study aimed to investigate the feasibility of forming aerobic granules from nicotin

Externí odkaz: https://doaj.org/article/83b2c98471fd4dbc8184182fb1d4e988

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Improving the Extraction of Tetracycline from Aqueous Solution by the Use of Acetone as an Adjuvant in ATPS Containing Poly(ethylene glycol) and Organic Salts and the Study of Its Phase Behavior

Autor: Seyed Ali Torabi, Fatemeh Samimi Choukami, Iman Nikkhah, Gholam Khayati

Publikováno v: Industrial & Engineering Chemistry Research. 62:7975-7986

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::55ac42d2643d117c918015cfc8e01a14
https://doi.org/10.1021/acs.iecr.3c00154

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Influence of Organic Salts on the Phase Equilibrium of Biphasic Systems Containing the Nonionic Surfactant (Triton X-100): Experiment and Correlation

Autor: Gholam Khayati, Fatemeh Ramzani, Seyede Elahe Mousaviafr, Sahar Rabizadeh Shahrestani

Publikováno v: Journal of Solution Chemistry. 52:251-261

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0d6c7779863e0b3f6f7c6d7dca36c5cd
https://doi.org/10.1007/s10953-022-01230-7

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Akademický článek

Optimization of micro hardness of nanostructure Cu-Cr-Zr alloys prepared by the mechanical alloying using artificial neural networks and genetic algorithm

Autor: Malihe Zeraati, Gholam Khayati

Publikováno v: Journal of Ultrafine Grained and Nanostructured Materials, Vol 51, Iss 2, Pp 183-192 (2018)

Cu–Cr-Zr alloys had wide applications in engineering applications such as electrical and welding industrial especially for their high strength, high electrical as well as acceptable thermal conductivities and melting points. It was possible to prep

Externí odkaz: https://doaj.org/article/3980bf7c48fc4affa35bb81caf5ff79e

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Akademický článek

Adaptive neuro-fuzzy inference system and neural network in predicting the size of monodisperse silica and process optimization via simulated annealing algorithm

Autor: Mehrdad Mahdavi jafari, Gholam Khayati

Publikováno v: Journal of Ultrafine Grained and Nanostructured Materials, Vol 51, Iss 1, Pp 43-52 (2018)

In this study, Back-propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS) methods were applied to estimate the particle size of silica prepared by sol-gel technique. Simulated annealing algorithm (SAA) employed to determ

Externí odkaz: https://doaj.org/article/bee17ba8706d49be947c92bb2f75b572

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Akademický článek

Phase Diagram, Equilibrium Data, and Correlation for Aqueous Two-Phase System Formed by Tetrahydrofuran and Sorbitol.

Autor: Khadijeh Pourkhanali¹ (AUTHOR), Gholam Khayati¹ (AUTHOR) khayati@guilan.ac.ir

Publikováno v: Theoretical Foundations of Chemical Engineering. Nov2021, Vol. 55 Issue 6, p1169-1177. 9p.

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Akademický článek

Hardness Optimization for Al6061-MWCNT Nanocomposite Prepared by Mechanical Alloying Using Artificial Neural Networks and Genetic Algorithm

Autor: Mehrdad Mahdavi Jafari, Soheil Soroushian, Gholam Khayati

Publikováno v: Journal of Ultrafine Grained and Nanostructured Materials, Vol 50, Iss 1, Pp 23-32 (2017)

Among artificial intelligence approaches, artificial neural networks (ANNs) and genetic algorithm (GA) are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (A

Externí odkaz: https://doaj.org/article/f96057adf8db4389aab6c7af98ffc60e

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Akademický článek

Kinetic parameters estimation of protease production using penalty function method with hybrid genetic algorithm and particle swarm optimization

Autor: Mahsa Ghovvati, Gholam Khayati, Hossein Attar, Ali Vaziri

Publikováno v: Biotechnology & Biotechnological Equipment, Vol 30, Iss 2, Pp 404-410 (2016)

Almost all optimization techniques are restricted by the problems' dimensions and large search spaces. This research focuses on a special hybrid method combining two meta-heuristic techniques, genetic algorithms (GA) and particle swarm optimization (

Externí odkaz: https://doaj.org/article/774f298d89e943d3ba1e0be6d83ee3c0

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