An Effective Data-Driven Model for Predicting Energy Consumption of Long-Distance Oil Pipelines-Reference-Cited by-同舟云学术

An Effective Data-Driven Model for Predicting Energy Consumption of Long-Distance Oil Pipelines

Published:2022-05 Issue:2 Volume:13 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Lu Hongfang¹,Xu Zhao-Dong²,Azimi Mohammadamin³,Fu Lingdi⁴,Wang Yijia⁵

Affiliation:

1. Associate Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China.

2. Professor, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast Univ., Nanjing 210096, China (corresponding author).

3. Senior Structural Engineer, GeoEngineers, Inc., 13220 Evening Creek Dr S Suite 115, San Diego, CA 92128.

4. Engineer, Safety, Environment and Technology Supervision Research Institute, PetroChina Southwest Oil & Gasfield Company, Chengdu 610041, China.

5. Engineer, Sichuan Special Equipment Inspection and Research Institute, Chengdu 610000, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29PS.1949-1204.0000637

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3. Forecasting energy consumption of long-distance oil products pipeline based on improved fruit fly optimization algorithm and support vector regression

4. Kennedy J. and R. Eberhart. 1995. “Particle swarm optimization.” In Vol. 4 of Proc. of ICNN’95-Int. Conf. on Neural Networks 1942–1948. New York: IEEE.

5. Study on prediction method of energy consumption in crude oil pipelines;Li X.;Oil Gas Storage Transp.,2009

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