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We discuss in this paper how the results of the discipline known as Knowledge Management could improve some types of Environmental Systems. In particular we discuss Environmental Decision Support Systems (EDSS). In the last decade, EDSS emerged as a suitable software tool to support control decision-making to maximize the performance of a system and to(More)
Wastewater Treatment Plants (WWTPs) control and prediction under a wide range of operating conditions is an important goal in order to avoid breaking of environmental balance, keep the system in stable operating conditions and suitable decision-making. In this respect, the availability of models characterizing WWTP behaviour as a dynamic system is a(More)
The complexity of environmental problems makes necessary the development and application of new tools capable of processing not only numerical aspects, but also experience from experts and wide public participation, which are all needed in decision-making processes. Environmental decision support systems (EDSSs) are among the most promising approaches to(More)
The step of identifying to which class of operational situation belongs the current environmental system (ES) situation is a key element to build successful environmental decision support systems (EDSS). This diagnosis phase is especially difficult due to multiple features involved in most environmental systems. It is not an easy task for environmental(More)
Artificial intelligence techniques, including machine learning methods, and statistical techniques have shown promising results as decision support tools, because of their capabilities of knowledge discovery, heuristic reasoning and working with uncertain and qualitative information. Wastewater treatment plants are complex environmental processes that are(More)
In recent years, several researchers have studied the suitability of CBR to cope with dynamic or continuous or temporal domains. In these domains , the current state depends on the past temporal states. This feature really makes difficult to cope with these domains. This means that classical individual case retrieval is not very accurate, as the dynamic(More)
This paper proposes a risk assessment model for settling problems of microbiological origin in activated sludge systems (filamentous bulking, foaming and rising sludge). The aim of the model is not to diagnose microbiology-related solids separation problems with absolute certainty but to quantify in dynamic scenarios whether simulated operational procedures(More)
Over recent years a huge library of data mining algorithms has been developed to tackle a variety of problems in fields such as medical imaging and network traffic analysis. Many of these techniques are far more flexible than more classical modelling approaches and could be usefully applied to data-rich environmental problems. Certain techniques such as(More)