A novel soft sensor model based on artificial neural network in the fermentation process

2011 ◽  
Vol 10 (85) ◽  
Author(s):  
Guohai Liu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fermentation Process ◽  
Soft Sensor ◽  
Model Based ◽  
Sensor Model ◽  
Artificial Neural

A robust soft sensor to monitor 1,3‐propanediol fermentation process by Clostridium butyricum based on artificial neural network

2020 ◽  
Vol 117 (11) ◽  
pp. 3345-3355
Author(s):  
Ai‐Hui Zhang ◽  
Kai‐Yi Zhu ◽  
Xiao‐Yan Zhuang ◽  
Lang‐Xing Liao ◽  
Shi‐Yang Huang ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fermentation Process ◽  
Soft Sensor ◽  
Clostridium Butyricum ◽  
Artificial Neural

scholarly journals Stochastic reserving with a stacked model based on a hybridized Artificial Neural Network

2021 ◽  
Vol 163 ◽  
pp. 113782
Author(s):  
Eduardo Ramos-Pérez ◽  
Pablo J. Alonso-González ◽  
José Javier Núñez-Velázquez
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Model Based ◽  
Artificial Neural

scholarly journals CONSTRUCTION OF NEURAL NETWORK MODEL FOR STUDYING OF CRYSTAL STRUCTURES PROPERTIES

2021 ◽  
Author(s):  
Olga Uvarova ◽  
Sergey Uvarov
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Total Energy ◽  
Crystal Structures ◽  
Network Model ◽  
Neural Network Model ◽  
Cohesive Energy ◽  
Computational Experiment ◽  
Model Based ◽  
Artificial Neural

The paper considers a mechanism for constructing a model based on artificial neural network for obtaining the values of the cohesive energy of a system of atoms. Cohesive energy allows for calculation of total energy of system. It is one of the most important characteristics of a structure. A computational experiment is carried out for one-component crystal structures of Si, Ge and C.

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