Fuzzy Filtering: A Mathematical Theory and Applications in Life Science

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Toward a relational concept of uncertainty: about knowing too little, knowing too differently, and accepting not to know

Uncertainty of late has become an increasingly important and controversial topic in water resource management, and natural resources management in general. Diverse managing goals, changing environmental conditions, conflicting interests, and lack of predictability are some of the characteristics that decision makers have to face. This has resulted in the application and development of strategies such as adaptive management, which proposes flexibility and capability to adapt to unknown conditions as a way of dealing with uncertainties. However, this shift in ideas about managing has not always been accompanied by a general shift in the way uncertainties are understood and handled. To improve this situation, we believe it is necessary to recontextualize uncertainty in a broader way¿relative to its role, meaning, and relationship with participants in decision making¿because it is from this understanding that problems and solutions emerge. Under this view, solutions do not exclusively consist of eliminating or reducing uncertainty, but of reframing the problems as such so that they convey a different meaning. To this end, we propose a relational approach to uncertainty analysis. Here, we elaborate on this new conceptualization of uncertainty, and indicate some implications of this view for strategies for dealing with uncertainty in water management. We present an example as an illustration of these concepts. Key words: adaptive management; ambiguity; frames; framing; knowledge relationship; multiple knowledge frames; natural resource management; negotiation; participation; social learning; uncertainty; water managemen

Influence of the Tunnel Shape on Shotcrete Lining Stresses

Tunnel excavation is frequently carried out in rock masses by the drill and blast method and the final shape of the tunnel boundary can be irregular due to overbreaks. In order to investigate the effects of overbreaks a study of the effect of tunnel boundary irregularity has been carried out. This is done developing a computational tool able to take into account fuzzy variables (i.e., thickness of the beams of the bedded spring approach used for the model). The obtained results show that irregularity effects should be considered when a shotcrete lining is used as the final tunnel lining (for the case where the tunneling procedure does not permit a smooth surface to be obtained). This is crucial to obtain a durable linin

Using ANFIS in joint dynamics of monetization, financial development, public debt and unemployment analysis

Purpose: The modern concepts of contemplating joint dynamics of monetary policy effects on economic growth and its indicators require an indirect approach based on empirical research of mainly financial infrastructure, competitiveness of the financial markets and current economic conditions. Meanwhile, the problems of unemployment and the structure of employment within these concepts are most frequently linked with the polarization of the labor market and two important factors, that is, the effects of growth on unemployment and the fact that technological changes affect the changes in salary ranges. Methodology: By using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the set of data from 1995 to 2016, this paper analyzes these issues through a prism of established balances between the labor and financial markets, i.e., the monetization of economy (M1/GDP), financial development (Loans/GDP) and the share of gross government debt in GDP (government gross debt/GDP). Results: The proposed model suggests that the rate of unemployment is conditioned by the financial cycle and monetary policy (M1/GDP, Loans/GDP), as well as the business cycle and fiscal policy (gross d/BDP) and that a controlled and properly directed level of monetization of the economy (M1/BDP) and financial development measured as Loans/GDP can be “sufficient” for economic growth. Conclusion: Waiting in the “monetary union lobby”, i.e., waiting for the ERM II exchange mechanism can last longer than the set deadlines, leading to the need for Croatian economic policy to optimize monetary and fiscal policy measures in order to increase economic growth and reduce unemployment

An intelligent framework for monitoring student performance using fuzzy rule-based linguistic summarisation

Monitoring students' activity and performance is vital to enable educators to provide effective teaching and learning in order to better engage students with the subject and improve their understanding of the material being taught. We describe the use of a fuzzy Linguistic Summarisation (LS) technique for extracting linguistically interpretable scaled fuzzy weighted rules from student data describing prominent relationships between activity / engagement characteristics and achieved performance. We propose an intelligent framework for monitoring individual or group performance during activity and problem based learning tasks. The system can be used to more effectively evaluate new teaching approaches and methodologies, identify weaknesses and provide more personalised feedback on learner's progress. We present a case study and initial experiments in which we apply the fuzzy LS technique for analysing the effectiveness of using a Group Performance Model (GPM) to deploy Activity Led Learning (ALL) in a Master-level module. Results show that the fuzzy weighted rules can identify useful relationships between student engagement and performance providing a mechanism allowing educators to transparently evaluate teaching and factors effecting student performance, which can be incorporated as part of an automated intelligent analysis and feedback system

Intelligent Modelling of the Environmental Behaviour of Chemicals

In view of the new European Union chemical policy REACH (Registration, Evaluation, and Authorization of Chemicals), interest in "non-animal" methods for assessing the risk potentials of chemicals towards human health and environment has increased. The incapability of classical modelling approaches in the complex and ill-defined modelling problems of chemicals' environmental behavior, together with an availability of large computing power in modern times raise an interest in applying computational models inspired by the approaches coming from the area of artificial intelligence. This thesis is devoted to promote the applications of neuro/fuzzy techniques in assessing the environmental behavior of chemicals. Some of the bottlenecks lying in the neuro/fuzzy modelling of chemicals' behavior towards environment have been identified and the solutions have been provided based on the techniques of computational intelligence.Diese Dissertation beinhaltet die Anwendung von neuronalen bzw. fuzzy Netzen, um das Umweltverhalten von Chemikalien beurteilen zu können. In dieser Arbeit werden die Probleme der Modellierung von Chemikalien gegenüber der Umwelt aufgezeigt und Lösungen angeboten. Die Lösungen basieren auf künstlichen Intelligenztechniken. Die Qualität der Modellierungstechniken hängt von mehreren Faktoren ab, z.B. der Eingabe, der Struktur und so weiter. In vielen Fällen werden keine geeigneten Resultate erhalten. So läuft es auf die Entwicklung eines Modells mit einer niedrigen Generalisierungsfähigkeit (Verallgemeinerungsfähigkeit)hinaus