Robust Data-Driven Soft Sensors for Online Monitoring of Volatile Fatty Acids in Anaerobic Digestion Processes

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@Article{Kazemi:2020:Processes,

• author = "Pezhman Kazemi and Jean-Philippe Steyer and Christophe Bengoa and Josep Font and Jaume Giralt",
• title = "Robust Data-Driven Soft Sensors for Online Monitoring of Volatile Fatty Acids in Anaerobic Digestion Processes",
• journal = "Processes",
• year = "2020",
• month = jan,
• volume = "8",
• number = "1",
• pages = "67",
• keywords = "genetic algorithms, genetic programming, ANN, SVM, anaerobic digestion, soft sensor, data driven, neural network, environmental sciences, environmental engineering",
• publisher = "HAL CCSD; MDPI",
• ISSN = "2227-9717",
• URL = "https://hal.inrae.fr/hal-02535092",
• URL = "https://hal.inrae.fr/hal-02535092/document",
• URL = "https://hal.inrae.fr/hal-02535092/file/Kazemi-Processes-2020-CC-BY.pdf",
• DOI = "doi:10.3390/pr8010067",
• abstract = "The concentration of volatile fatty acids (VFAs) is one of the most important measurements for evaluating the performance of anaerobic digestion (AD) processes. In real-time applications, VFAs can be measured by dedicated sensors, which are still currently expensive and very sensitive to harsh environmental conditions. Moreover, sensors usually have a delay that is undesirable for real-time monitoring. Due to these problems, data-driven soft sensors are very attractive alternatives. This study proposes different data-driven methods for estimating reliable VFA values. We evaluated random forest (RF), artificial neural network (ANN), extreme learning machine (ELM), support vector machine (SVM) and genetic programming (GP) based on synthetic data obtained from the international water association (IWA) Benchmark Simulation Model No. 2 (BSM2). The organic load to the AD in BSM2 was modified to simulate the behaviour of an anaerobic co-digestion process. The prediction and generalisation performances of the different models were also compared. This comparison showed that the GP soft sensor is more precise than the other soft sensors. In addition, the model robustness was assessed to determine the performance of each model under different process states. It is also shown that, in addition to their robustness, GP soft sensors are easy to implement and provide useful insights into the process by providing explicit equations.",
• annote = "Departament d{'}Enginyeria Quimica ; Universitat Rovira i Virgili; Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE) ; Institut national d{'}etudes superieures agronomiques de Montpellier (Montpellier SupAgro) ; Institut national d'enseignement superieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement superieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l{'}Agriculture, l{'}Alimentation et l{'}Environnement (INRAE); Departament d'Enginyeria Electronica [Barcelona] ; Universitat Autonoma de Barcelona [Barcelona] (UAB); Ministerio de Economia, Industria y Competitividad; the Ministerio de Ciencia, Innovacion y Universidades, the Agencia Estatal de Investigacion (AEI) ; European Regional Development Fund (ERDF), (CTM2015-67970-P, RTI2018-096467-B-I00).; Universitat Rovira i Virgili (URV), (2017PFR-URV-B2-33, 2019OPEN) ; Fundacio Bancaria {"}la Caixa{"} (2017ARES-06).",
• bibsource = "OAI-PMH server at api.archives-ouvertes.fr",
• contributor = "Departament d{'}Enginyeria Quimica and Laboratoire de Biotechnologie de l'Environnement [Narbonne] and Departament d'Enginyeria Electronica [Barcelona] and Industria y Competitividad Ministerio de Economia",
• identifier = "hal-02535092; DOI: 10.3390/pr8010067; WOS: 000516825300034",
• language = "en",
• oai = "oai:HAL:hal-02535092v1",
• relation = "info:eu-repo/semantics/altIdentifier/doi/10.3390/pr8010067",
• rights = "http://creativecommons.org/licenses/by/>; info:eu-repo/semantics/OpenAccess",

}

Genetic Programming entries for Pezhman Kazemi Jean-Philippe Steyer Christophe Bengoa Josep Font Capafons Jaume Giralt

Citations