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Accueil du site Doctorat Grèce Fuzzy hybrid models for the analysis and assessment of hydrological extreme events

** Titre : ** Fuzzy hybrid models for the analysis and assessment of hydrological extreme events

** Auteur : ** Papadopoulos, Christoforos of Apostolos

** Etablissement de soutenance : ** Democritus University of Thrace (DUTH)

** Grade : ** Doctor of Philosophy (PhD) 2022

**Résumé partiel **

Hydrological extremes events, such as floods and droughts, are natural disasters that are caused by climatic and hydrometeorological disturbances. They have a direct or indirect impact not only over the ecological systems but also on a wide spectrum of operations of anthropogenic systems and they are the cause of loss of human lives.In particular, over the past few decades there is a growing concern in the scientific community about the catastrophic dimensions of these phenomena as increasing trends have been observed both in terms of the frequency of their occurrence and the severity of flood events and drought periods.Fuzzy logic and the theory of fuzzy sets is a relatively new mathematical consideration with which multiple problems related to these phenomena can be approached. Lotfi A. Zadeh (1921-2017), an Iranian−American electrical engineer, was the first to introduce fuzzy logic in 1965. Fuzzy logic is a many−valued logic where variables can take infinite values in a range between 0 and 1 (including the limit values) thus generalizing the classic two−valued logic and classic sets. It has the ability to simulate the human way of thinking either by developing autonomous tools or while used in combination with other methods, and is widely applied in different scientific fields.In this direction, the present doctoral dissertation develops and applies the following innovative hybrid methodologies which are based on the principles of fuzzy logic and the theory of fuzzy sets.A hybrid fuzzy probabilistic methodology was developed based on fuzzy linear regression method and the frequency factor method in order to couple the observed probabilities and the theoretical probability distribution which is based on the historical sample. Initially, the frequency factor KT was calculated with the use of the empirical probabilities in assumptions of a theoretical probability distribution, and then it was carried out a fuzzy linear regression between the considered physical variable (dependent variable) and KT (independent variable). Additionally, it was achieved simultaneously a fuzzy estimation of the mean value and the standard deviation. The proposed methodology was applied to data sets of annual cumulative rainfall and annual cumulative streamflow in order to analyse and classify meteorological and hydrological drought, respectively. It can also be applied to the frequency analysis of flood events by additionally taking into account the probability distribution of the maximum type I (Gumbel distribution). Furthermore, it was achieved a fuzzy classification of meteorological and hydrological drought which was based on the produced fuzzy linear relations.For the analysis and classification of hydrological and meteorological drought, it was used the Tanaka model (1987) as well as a modified fuzzy linear regression model regarding the objective function. Both of the models result to a constraint optimization problem where all the observed data must be included in the produced fuzzy band.

** Mots clés : ** Fuzzy logic ; Fuzzy sets ; Fuzzy linear regression ; Fuzzy estimators ; Fuzzy pattern recognition ; Fuzzy inference systems ; Fuzzy Analytic Hierarchy Process ; Multicriteria analysis ; Drought ; Drought indices ; Flood ; Vulnerability ; Managed aquifer systems ; Conjunctive use of groundwater and surface water ; Alluvial aquifers

Page publiée le 14 décembre 2022