Data-driven soft-sensor modelling for air cooler system pH values based on a fast search pruned-extreme learning machine-Reference-Cited by-同舟云学术

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Data-driven soft-sensor modelling for air cooler system pH values based on a fast search pruned-extreme learning machine

Published:2016-12-15 Issue:2 Volume:12 Page:186-195
ISSN:1932-2135
Container-title:Asia-Pacific Journal of Chemical Engineering
language:en
Short-container-title:Asia-Pac. J. Chem. Eng.

Author:

Ye Yisha¹,Ren Jia¹,Wu Xuehua¹,Ou Guofu¹,Jin Haozhe¹

Affiliation:

1. Department of Automation; Zhejiang Sci-Tech University; Hangzhou 310018 Zhejiang China

Funder

Zhejiang Public Technology Research Program

National Natural Science Fund Committee-Shenhua Group Co., Ltd. Coal Joint Fund

Zhejiang Provincial Natural Science Foundation of China

Publisher

Wiley

Subject

Waste Management and Disposal,Renewable Energy, Sustainability and the Environment,General Chemical Engineering

Reference38 articles.

1. Assessment of corrosion in low carbon steel tubes of Shiraz refinery air coolers;Jahromi;Engineering Failure Analysis,2005

2. Corrosion of Galvanised steel cord reinforcement in HDPE composite pipes in petroleum production;Jiang;Corros. Eng. Sci. Techn.,2014

3. Selective combination of multiple neural networks for improving model prediction in nonlinear systems modeling through forward selection and backward elimination;Ahmad;Neurocomputing,2009

4. A methodology for modeling batch reactors using generalized dynamic neural networks;Kashani;Chemical Engineering Journal,2010

5. Method for plant data-based process modeling in soft-sensor development;Dražen;Automatika,2011

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4. Numerical simulation and simplified calculation method for heat exchange performance of dry air cooler in natural gas pipeline compressor station;Energy Science & Engineering;2020-02-20

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