Intelligent prediction of aliphatic and aromatic hydrocarbons in Caspian Sea sediment using a neural network based on particle swarm optimization-Reference-Cited by-同舟云学术

Intelligent prediction of aliphatic and aromatic hydrocarbons in Caspian Sea sediment using a neural network based on particle swarm optimization

Published:2019-10-07 Issue:24 Volume:37 Page:2364-2373
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Amin Javad Sayyad¹²,Kuyakhi Hossein Rajabi¹,Bahadori Alireza³

Affiliation:

1. Department of Chemical Engineering, University of Guilan, Rasht, Iran;

2. Department of Marine Industries, Caspian Sea Basin Research Center, University of Guilan, Rasht, Iran;

3. School of Environment, Science & Engineering, Southern Cross University, Lismore, Australia

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2018.1542439

Reference35 articles.

1. Estimation of asphaltene precipitation in light, medium and heavy oils: experimental study and neural network modeling

2. Distribution and sources of polycyclic aromatic hydrocarbons in the surface sediments of Gorgan Bay, Caspian Sea

3. Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches

4. Improved estimation of Cetane number of fatty acid methyl esters (FAMEs) based biodiesels using TLBO-NN and PSO-NN models

5. Seasonal variation of polycyclic aromatic hydrocarbons in the surface sediments of the southern Caspian Sea

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