Predicting vapor pressures using neural networks-Reference-Cited by-同舟云学术

Predicting vapor pressures using neural networks

Published:1997-03 Issue:5 Volume:31 Page:741-753
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Potukuchi Sudhakar,Wexler Anthony S.

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

Reference25 articles.

1. Application of neural networks to particle shape classification;Bevan;J. Aerosol Sci.,1992

2. A neural network-based method for short term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrain;Boznar;Atmospheric Environment,1993

3. Thermodynamic properties of aqueous (NH4)2SO4 to high supersaturation as a function of temperature;Clegg;J. chem. engng Data,1995

4. Application of multicomponent thermodynamic model to activities and thermal properties of 0–40 mol/kg aqueous sulfuric acid from < 200 to 328 K;Clegg;J. chem. engng. Data,1995

5. Thermodynamics of multicomponent, miscible, ionic solutions: generalized equations for symmetrical electrolytes;Clegg;J. phys. Chem.,1992

Cited by 29 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. Vapor–liquid equilibrium estimation of n-alkane/nitrogen mixtures using neural networks;Journal of Computational and Applied Mathematics;2022-07

2. Prediction of Formation Conditions of Gas Hydrates Using Machine Learning and Genetic Programming;Machine Learning for Societal Improvement, Modernization, and Progress;2022-06-24

3. Conservation laws in a neural network architecture: enforcing the atom balance of a Julia-based photochemical model (v0.2.0);Geoscientific Model Development;2022-04-28

4. Artificial Neural Network;Applications of Nature-Inspired Computing in Renewable Energy Systems;2022

5. Prediction of gas hydrate formation using empirical equations and data-driven models;Materials Today: Proceedings;2021