
An environmental decision-support system for wastewater treatment
Bridging environmental science and information and communication technology
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This book bridges two disciplines: wastewater management and artificial intelligence. Wastewater management as a discipline operates using a range of different approaches and methods which include: manual control, on-line automatic control, numerical or non-numerical models, statistical models and simulation models. The book characterizes an interdisciplinary research on artificial intelligence techniques (rule-based reasoning, case-based reasoning, ontologies and planning) applied to environmental decision-support systems. The integrated architecture's design of this application, the OntoWEDS...
This book bridges two disciplines: wastewater management and artificial intelligence. Wastewater management as a discipline operates using a range of different approaches and methods which include: manual control, on-line automatic control, numerical or non-numerical models, statistical models and simulation models. The book characterizes an interdisciplinary research on artificial intelligence techniques (rule-based reasoning, case-based reasoning, ontologies and planning) applied to environmental decision-support systems. The integrated architecture's design of this application, the OntoWEDSS system, augments classic reasoning systems (rule-based reasoning and case-based reasoning) with a domain ontology about the management of wastewater treatment plants. The integration of the newly created WaWO ontology provides a more flexible management capability to OntoWEDSS. The construction of the OntoWEDSS decision support system is based on a specific case study but the system is also of general interest, given that its ontology-underpinned architecture can be applied to any wastewater treatment plant and, at an appropriate level of abstraction, to other environmental domains.