Intelligent Optimal Control Model of Selection Pressure for Rapid Culture of Aerobic Granular Sludge Based on Machine Learning and Simulated Annealing Algorithm

Author:

Liu Zhe,Lei Jie,Cheng Linshan,Yang Rushuo,Yang Zhuangzhuang,Shi Bingrui,Wang Jiaxuan,Zhang Aining,liu yongjun

Publisher

Elsevier BV

Reference37 articles.

1. A review of mechanistic and data-driven models of aerobic granular sludge;G Achari;Journal of Environmental Chemical Engineering,2022

2. Performance, microbial community evolution and neural network modeling of single-stage nitrogen removal by partial-nitritation/anammox process;P Antwi;Bioresource Technology,2019

3. Modeling the performance of Single-stage Nitrogen removal using Anammox and Partial nitritation (SNAP) process with backpropagation neural network and response surface methodology;P Antwi;Science of the Total Environment,2019

4. Spatial Planning of Marine Protected Areas (MPAs) in the Southern Caspian Sea: Comparison of Multi-Criteria Evaluation (MCE) and Simulated Annealing Algorithm;D Ashtab;Journal of Marine Science and Engineering,2024

5. Quantile Regression Boosting Tree and Its Application;C Cai;Journal of Systems Science and Mathematical Sciences,2022

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