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| Hybrid Model of Measuring Biogas Yield in Anaerobic Digestion Process Based on Incorporated Bio-Kinetic Model with Support Vector Machine Model |
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| DOI：10.11980/j.issn.0254-508X.2017.03.006 |
| Key Words:anaerobic digestion biogas flow rate kinetic model Support Vector Machine model particle swarm optimization |
| Fund Project:国家自然科学基金资助（项目编号：31570568，31670585）;制浆造纸工程国家重点实验室开放基金(NO.201535);广东省高层次人才基金(NO.201339);广州市科技计划项目（项目编号：201607010079，201607020007）;广东省科技计划项目（项目编号：2016A020221005）。 |
| Author Name | Affiliation | | 刘 林1 | 1.华南理工大学环境与能源学院，广东广州,510006 | | 谢 彬1 | 1.华南理工大学环境与能源学院，广东广州,510006 | | 马邕文1,2,3,* | 1.华南理工大学环境与能源学院，广东广州,510006；2.华南理工大学工业聚集区污染控制与生态修复教育部重点实验室,广东广州,510006；3.华南理工大学制浆造纸工程国家重点实验室,广东广州,510640 | | 万金泉1,2,3 | 1.华南理工大学环境与能源学院，广东广州,510006；2.华南理工大学工业聚集区污染控制与生态修复教育部重点实验室,广东广州,510006；3.华南理工大学制浆造纸工程国家重点实验室,广东广州,510640 | | 王 艳1,2,3 | 1.华南理工大学环境与能源学院，广东广州,510006；2.华南理工大学工业聚集区污染控制与生态修复教育部重点实验室,广东广州,510006；3.华南理工大学制浆造纸工程国家重点实验室,广东广州,510640 |
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| Abstract:Lack of AD process control and analysis is believed to be one of the main limitations for effective organic matter degradation. Biogas flow rate and component as commonly monitoring indicators indicate the overall process performance. The objective of this work was to implement a strategy to simultaneously monitor and predict the biogas flow rate using a hybrid model, which combined kinetic model and a traditional Support Vector Machine model (SVM) optimized by particle swarm optimization algorithm (PSO). For the training and verification of the models, a data set with 159 samples was used, which were obtained using a lab-scale AD reactor system. The results demonstrated that the hybrid model had a satisfying predicting performance. The R value of the traditional model was 86.71%. And compared with traditional model, the performance of the hybrid model was improved significantly the R value of the hybrid model was 95.73%. Furthermore, the hybrid model gave a successful window, which was a good reference for the modeling study of AD process. |
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