Improved predictions of wellhead choke liquid critical-flow rates: Modelling based on hybrid neural network training learning based optimization

标题
Improved predictions of wellhead choke liquid critical-flow rates: Modelling based on hybrid neural network training learning based optimization
作者
关键词
Liquid critical-flow rate, Non-linear regression, Artificial neural network, Teaching-learning-based optimization, Empirical wellhead coke flow rate published correlations, Relevancy factor
出版物
FUEL
Volume 207, Issue -, Pages 547-560
出版商
Elsevier BV
发表日期
2017-07-05
DOI
10.1016/j.fuel.2017.06.131

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Create your own webinar

Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.

Create Now

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started