Deep learning model based on Bayesian optimization for predicting the infinite dilution activity coefficients of ionic liquid-solute systems-Reference-Cited by-同舟云学术

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Deep learning model based on Bayesian optimization for predicting the infinite dilution activity coefficients of ionic liquid-solute systems

Published:2023-11 Issue: Volume:126 Page:107127
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Fan Dingchao,Zhu Wenguang,Chen Yusen,Xue Ke,Liu Tianxiong,Cui Peizhe,Qi Jianguang,Zhu Zhaoyou,Wang Yinglong

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference51 articles.

1. Tensorflow: a System for Large-Scale Machine Learning;Abadi,2016

2. The correlation and prediction of infinite dilution activity coefficients of compounds in water at 298.15 K;Abraham;Fluid Phase Equil.,2017

3. Sigma profiles in deep learning: towards a universal molecular descriptor;Abranches;Chem. Commun.,2022

4. Machine-learning model prediction of ionic liquids melting points;Acar;Appl. Sci.,2022

5. Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: long short-term memory (LSTM) network coupled with wavelet transform;Alizamir;Eng. Appl. Artif. Intell.,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of ionic liquid surface tension via a generalized interpretable Structure‐Surface Tension Relationship model;AIChE Journal;2024-08-07

2. Modeling and estimation of water activity for the ionic-liquid-based aqueous ternary systems by smart paradigms;Journal of the Taiwan Institute of Chemical Engineers;2024-04

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