Indian Journal of Science and Technology

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The Prediction of Cloud Point Temperature in Wax and Pure Paraffin Depositions by using a PSO Based ANN Approach


Affiliations
1 Department of Computer, Najaf Abad Branch, Islamic Azad University, Najaf Abad, Iran, Islamic Republic of
2 Department of Computer, Qom Branch, Islamic Azad University, Qom, Iran, Islamic Republic of
 

Objectives: Predicting the Cloud Point Temperatures in Wax and Pure Paraffin Depositions which can help oil experts make substantial decisions to have less heavy material deposition in crude (oil). Methods/Statistical Analysis: In this paper, we use a PSO based ANN approach to predict the cloud point temperature of depositions, which has been designed based on the most important parameters that are related to cloud point temperature. Solvent molecular weights, solute molecular weights, and solute weight fraction are the main parameters that have been considered, while observing the cloud point temperature amounts. Findings: By predicting factors that make sediment happen, we eliminate or reduce the deposition of action. The modeled results show 99% for test dataset in both used depositions. Application/Improvements: The proposed method improves the results to achieve more precision results compared to the previous related works.
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  • The Prediction of Cloud Point Temperature in Wax and Pure Paraffin Depositions by using a PSO Based ANN Approach

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Authors

Maryam Joudaki
Department of Computer, Najaf Abad Branch, Islamic Azad University, Najaf Abad, Iran, Islamic Republic of
Alireza Seddighi
Department of Computer, Qom Branch, Islamic Azad University, Qom, Iran, Islamic Republic of

Abstract


Objectives: Predicting the Cloud Point Temperatures in Wax and Pure Paraffin Depositions which can help oil experts make substantial decisions to have less heavy material deposition in crude (oil). Methods/Statistical Analysis: In this paper, we use a PSO based ANN approach to predict the cloud point temperature of depositions, which has been designed based on the most important parameters that are related to cloud point temperature. Solvent molecular weights, solute molecular weights, and solute weight fraction are the main parameters that have been considered, while observing the cloud point temperature amounts. Findings: By predicting factors that make sediment happen, we eliminate or reduce the deposition of action. The modeled results show 99% for test dataset in both used depositions. Application/Improvements: The proposed method improves the results to achieve more precision results compared to the previous related works.

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DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i31%2F115979