Runda Jia

Orcid: 0000-0002-8586-243X

According to our database1, Runda Jia authored at least 13 papers between 2012 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

2012
2014
2016
2018
2020
2022
2024
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Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Robust operating performance assessment of flotation processes using convolutional neural networks and feature learning.
Adv. Eng. Informatics, 2025

2024
Application of Robust Model Predictive Control Using Principal Component Analysis to an Industrial Thickener.
IEEE Trans. Control. Syst. Technol., May, 2024

Stable predictive control of continuous stirred-tank reactors using deep learning.
Inf. Sci., 2024

Sample-efficient reinforcement learning with knowledge-embedded hybrid model for optimal control of mining industry.
Expert Syst. Appl., 2024

2023
Safe reinforcement learning for industrial optimal control: A case study from metallurgical industry.
Inf. Sci., November, 2023

Collaborative Optimization Framework for the Industrial Thickening-Dewatering Process Based on Mixed Integer Linear Programming.
IEEE Trans. Instrum. Meas., 2023

2022
A general data-driven nonlinear robust optimization framework based on statistic limit and principal component analysis.
Comput. Chem. Eng., 2022

2021
A process transfer model-based optimal compensation control strategy for batch process using just-in-time learning and trust region method.
J. Frankl. Inst., 2021

2020
Transfer learning for end-product quality prediction of batch processes using domain-adaption joint-Y PLS.
Comput. Chem. Eng., 2020

2019
Ensemble regularized local finite impulse response models and soft sensor application in nonlinear dynamic industrial processes.
Appl. Soft Comput., 2019

Gold Recovery Modeling Based on Interval Prediction for a Gold Cyanidation Leaching Plant.
IEEE Access, 2019

2017
Rapid Modeling Method for Performance Prediction of Centrifugal Compressor Based on Model Migration and SVM.
IEEE Access, 2017

2012
Real-time product quality control for batch processes based on stacked least-squares support vector regression models.
Comput. Chem. Eng., 2012


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