# Artificial Neural Network and its Application Research Progress in Distillation

arXiv: https://arxiv.org/abs/2110.01449 · HTML: https://mlsanity.com/paper/2110.01449/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 53 references that are in the map.
- First posted on arXiv 1 Oct 2021.

## Builds on (most cited first, 4 of 4)

- [Distributionally Robust Games: f-Divergence and Learning](https://mlsanity.com/paper/1702.05371/) (2017)
- [Neural network algorithm and its application in reactive distillation](https://mlsanity.com/paper/2011.09969/) (2020)
- [Study on the simulation control of neural network algorithm in thermally coupled distillation](https://mlsanity.com/paper/2102.03506/) (2021)
- [Application of Neural Network Algorithm in Propylene Distillation](https://mlsanity.com/paper/2104.01774/) (2021)

## Abstract (arXiv)

Artificial neural networks learn various rules and algorithms to form different ways of processing information, and have been widely used in various chemical processes. Among them, with the development of rectification technology, its production scale continues to expand, and its calculation requirements are also more stringent, because the artificial neural network has the advantages of self-learning, associative storage and high-speed search for optimized solutions, it can make high-precision simulation predictions for rectification operations, so it is widely used in the chemical field of rectification. This article gives a basic overview of artificial neural networks, and introduces the application research of artificial neural networks in distillation at home and abroad.