Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A Knowledge-based System for the Diagnosis of Waste-Water Treatment Plants
IEA/AIE '92 Proceedings of the 5th international conference on Industrial and engineering applications of artificial intelligence and expert systems
Business Process Management: Concepts, Languages, Architectures
Business Process Management: Concepts, Languages, Architectures
Verifiable agent interaction in abductive logic programming: The SCIFF framework
ACM Transactions on Computational Logic (TOCL)
ProM 4.0: comprehensive support for real process analysis
ICATPN'07 Proceedings of the 28th international conference on Applications and theory of Petri nets and other models of concurrency
An approach for temporal case-based reasoning: episode-based reasoning
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Interpolation representation of feedforward neural networks
Mathematical and Computer Modelling: An International Journal
25 years of applications of logic programming in Italy
A 25-year perspective on logic programming
Data-driven modeling approaches to support wastewater treatment plant operation
Environmental Modelling & Software
Advances in Artificial Neural Systems
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This paper proposes a modular architecture for the analysis and the validation of wastewater treatment processes. An algorithm using neural networks is used to extract the relevant qualitative patterns, such as ''apexes'', ''knees'' and ''steps'', from the signals acquired in the reaction tanks. These patterns, which show changes in the signals trend, are mapped to events in the process and logged using an appropriate XML format. The logs, in turn, are considered traces of the execution of a manufacturing process and validated using tools commonly applied for the Verification of Business Processes. The system has been applied to the data collected from a Sequencing Batch Reactor (SBR) for municipal wastewater treatment, equipped with probes for the on-line acquisition of signals such as pH, oxidation--reduction potential (ORP) and dissolved oxygen (DO). A SBR has turned out to be a suitable case study since the commonly acknowledged criteria for monitoring the biological processes (nitrification and denitrification) can be expressed in the form or qualitative constraints, which are easily translated into formal rules. The process logs, hence, are matched against these rules, which act as filters and quality classifiers.