Comparative evaluation of artificial neural networks for the performance prediction of Pt‐based catalysts in water gas shift reaction-Reference-Cited by-同舟云学术

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Comparative evaluation of artificial neural networks for the performance prediction of Pt‐based catalysts in water gas shift reaction

Published:2022-03-14 Issue:7 Volume:46 Page:9602-9620
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Intl J of Energy Research

Author:

Kim Changsu¹^ORCID,Kim Jiyong¹^ORCID

Affiliation:

1. School of Chemical Engineering Sungkyungkwan University Suwon Republic of Korea

Funder

Korea Institute of Energy Technology Evaluation and Planning

Ministry of Education

Publisher

Hindawi Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.7829

Reference51 articles.

1. Machine learning: Trends, perspectives, and prospects

2. Recent advances and applications of machine learning in solid-state materials science

3. A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics

4. Machine Learning in Catalysis, From Proposal to Practicing

5. A review of clustering techniques and developments

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1. Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater;International Journal of Biological Macromolecules;2024-10

2. Machine learning-enhanced optimal catalyst selection for water-gas shift reaction;Digital Chemical Engineering;2024-09

3. Advancing Hybrid Nanocatalyst Research: A Python-based Visualization of Similarity Analysis for Interdisciplinary and Sustainable Development;Current Nanoscience;2023-12-29

4. Mechanisms in the Catalytic Reduction of N2O by CO over the M13@Cu42 Clusters of Aromatic-like Inorganic and Metal Compounds;Molecules;2023-06-01

5. Early-Stage Evaluation of Catalyst Using Machine Learning Based Modeling and Simulation of Catalytic Systems: Hydrogen Production via Water–Gas Shift over Pt Catalysts;ACS Sustainable Chemistry & Engineering;2022-10-25

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