Les incertitudes épistémiques peuvent être réduites via des études supplémentaires (mesures labo, in situ, ou modélisations numériques, etc.). Nous nous concentrons ici sur celle "paramétrique" liée aux difficultés à évaluer quantitativement les paramètres d’entrée du modèle utilisé pour l’analyse des aléas géotechniques. Une stratégie de gestion possible est l’analyse de sensibilité, qui consiste à identifier la contribution (i.e. l’importance) des paramètres dans l’incertitude de l’évaluation de l’aléa. Des approches avancées existent pour conduire une telle analyse. Toutefois, leur application au domaine des aléas géotechniques se confronte à plusieurs contraintes : 1. le coût calculatoire des modèles numériques (plusieurs heures voire jours) ; 2. les paramètres sont souvent des fonctions complexes du temps et de l’espace ; 3. les données sont souvent limitées, imprécises voire vagues. Dans cette thèse, nous avons testé et adapté des outils statistiques pour surmonter ces limites. Une attention toute particulière a été portée sur le test de faisabilité de ces procédures et sur la confrontation à des cas réels (aléas naturels liés aux séismes, cavités et glissements de terrain) / Importance ranking of parameter uncertainties in geo-hazard assessments Epistemic uncertainty can be reduced via additional lab or in site measurements or additional numerical simulations. We focused here on parameter uncertainty: this corresponds to the incomplete knowledge of the correct setting of the input parameters (like values of soil properties) of the model supporting the geo-hazard assessment. A possible option tomanage it is via sensitivity analysis, which aims at identifying the contribution (i.e. the importance) of the different input parameters in the uncertainty on the final hazard outcome. For this purpose, advanced techniques exist, namely variance-basedglobal sensitivity analysis. Yet, their practical implementation faces three major limitations related to the specificities of the geo-hazard domain: 1. the large computation time cost (several hours if not days) of numerical models; 2. the parameters are complex functions of time and space; 3. data are often scarce, limited if not vague. In the present PhD thesis, statistical approaches were developed, tested and adapted to overcome those limits. A special attention was paid to test the feasibility of those statistical tools by confronting them to real cases (natural hazards related to earthquakes, cavities and landslides)

<p>Problemi klasifikacije i segmentacije digitalnih slika su veoma<br />aktuelni i zastupljeni u praksi. Potreba za modelima koji razmatraju<br />ovu problematiku u poslednjih nekoliko decenija ubrzanim tempom<br />poprima sve veći značaj i obim u svakodnevnom životu. Koriste se u<br />računarskoj grafici, prepoznavanju oblika, medicinskoj analizi slika,<br />saobraćaju, analizi dokumenata, pokreta i izraza lica i sl.<br />U okviru ove disertacije, predstavljeno istraživanje motivisano je<br />primenama razvijenih modela u klasifikaciji i segmentaciji<br />digitalnih slika. Istraživanje obuhvata dva segmenta. Ovi segmenti<br />povezani su terminom neodređenosti, koji je uz upotrebu adekvatnog<br />matematičkog aparata (teorije fazi skupova), ugrađen u modele razvije<br />za primenu u obradi slike.<br />Jedan pravac istraživanja baziran je na teoriji fazi skupova, t-<br />normama, t-konormama, operatorima agregacije i agregiranim<br />funkcijama rastojanja. U okviru toga, istraživanje je sprovedeno sa<br />struktuiranom matematičkom podlogom, izložene su osnovne<br />definicije, teoreme, kao i osobine korištenih operatora, prošireni<br />su teorijski koncepti t-normi i t-konormi. Definisani su novi tipovi<br />operatora agregacije i njihovom primenom konstruisane su nove<br />funkcije rastojanja, čija je upotreba diskutovana kroz uspešnost u<br />procesu segmentacije digitalnih slika.<br />Drugi pravac istraživanja, izložen u ovoj disertaciji, obuhvata više<br />inženjerski pristup rešavanju problema klasifikacije tekstura<br />digitalnih slika. U skladu sa tim, detaljno je analizirana i<br />diskutovana klasa lokalnih binarnih deskriptora teksture.<br />Inspirisana uspešnošću pomenute LBP klase deskriptora, uvedena je<br />jedna nova podfamilija &alpha;-deskriptora teksture. Uvedeni model<br />deskriptora formiran je na temeljima idejnih principa lokalnih<br />binarnih kodova i bazičnih pojmova iz teorije fazi skupova. Praktična<br />upotreba i značaj predstavljenog modela demonstrirani su kroz veoma<br />uspešne procese klasifikacije na nekoliko javno dostupnih baza slika.</p> / <p>Classification and segmentation problems of digital images is a very attractive<br />topic and has been making impact in many different applied disciplines. In the<br />past few decades, the demand for models that address these issues has been<br />gaining momentum and applications in everyday life. These models are used in<br />computer graphics, shape recognition, medical image analysis, traffic, document<br />analysis, facial movements and expressions, etc.<br />The research within this doctoral dissertation was motivated by the application of<br />developed methods in classification and segmentation tasks. The conducted<br />research covered two segments, which were linked by the term of indeterminacy,<br />with the usage of the theory of fuzzy sets, which is incorporated into methods<br />developed for application in image processing.<br />One direction of the research was founded on the theory of fuzzy sets, t-norms,<br />t-conorms, aggregation operators, and aggregated distance functions. Within this<br />framework, the research was conducted with a structured mathematical<br />background. Firstly, basic definitions, theorems and characteristics of the used<br />operators were presented, followed by the theoretical concepts of t-norms and tconorms<br />that were extended. New types of aggregation operators and distance<br />functions were defined, and finally, their contribution in the digital image<br />segmentation process was explored and discussed.<br />The second direction of the research presented in this dissertation involved more<br />of an engineering-type of approach to solving the problem of the classification of<br />digital image textures. To that end, a class of local binary texture descriptors<br />(LBPs) was analyzed and discussed in detail. Inspired by the results of the<br />above-mentioned LBP descriptors, one new sub-family of the $\alpha$-<br />descriptors was introduced by the author. The introduced descriptor model was<br />based on the conceptual principles of LBPs and basic definitions from the fuzzy<br />set theory. Its practical usage and importance were established and reflected in<br />very successful classification results, achieved in the application on several<br />publicly available image datasets.</p>

This thesis deals with the application of Markov chains for the production of concrete products. The theoretical part is focused on clarifying the concepts of risk management and describes the procedures for dealing with classical Markov chains. There are presented basics of fuzzy logic and finally there is explained the procedure using fuzzy logic in calculating of classical Markov chains in the subsection entitled Fuzzy Markov chains. The practical part describes production process, namely concrete pavements. On this production process is applied knowledge from the theoretical part and there is a comparison and evaluation of two methods of Marcov chains calculation (classic and fuzzy approach).

The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being described and fuzzy logic is explained. The hybrid neuro-fuzzy system stemming from ANFIS system is designed on the basis of artificial neural networks, fuzzy sets and fuzzy logic. The upper-mentioned systems' functionality has been demonstrated on an inverted pendulum controlling problem. The three controllers have been designed for the controlling needs - the first one is on the basis of artificial neural networks, the second is a fuzzy one, and the third is based on ANFIS system.  The thesis is aimed at comparing the described systems, which the controllers have been designed on the basis of, and evaluating the hybrid neuro-fuzzy system ANFIS contribution in comparison with particular theory solutions. Finally, some experiments with the systems are demonstrated and findings are assessed.

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This thesis focuses on fuzzy neural networks. The combination of the fuzzy logic and artificial neural networks leads to the development of more robust systems. These systems are used in various field of the research, such as artificial intelligence, machine learning and control theory. First, we provide a quick overview of underlying neural networks and fuzzy systems to explain fundamental ideas that form the basis of the fields, and follow with the introduction of the fuzzy neural network theory, classification and application. Then we describe a design and a realization of the fuzzy associative memory, as an example of these systems. Finally, we benchmark the realization using the pattern recognition and control tasks. The results are evaluated and compared against existing systems.

Le développement de la fabrication additive permet d'élaborer des pièces de forme extrêmement complexes, en particulier des structures alvéolaires ou "lattices", où l'allégement est recherché. Toutefois, cette technologie, en très forte croissance dans de nombreux secteurs d'activités, n'est pas encore totalement mature, ce qui ne facilite pas les corrélations entre les mesures expérimentales et les simulations déterministes. Afin de prendre en compte les variations de comportement, les approches multiparamétriques sont, de nos jours, des solutions pour tendre vers des conceptions fiables et robustes. L'objectif de cette thèse est d'intégrer des incertitudes matérielles et géométriques, quantifiées expérimentalement, dans des analyses de flambement. Pour y parvenir, nous avons, dans un premier temps, évalué différentes méthodes de substitution, basées sur des régressions et corrélations, et différentes réductions de modèles afin de réduire les temps de calcul prohibitifs. Les projections utilisent des modes issus soit de la décomposition orthogonale aux valeurs propres, soit de développements homotopiques ou encore des développements de Taylor. Dans un second temps, le modèle mathématique, ainsi créé, est exploité dans des analyses ensemblistes et probabilistes pour estimer les évolutions de la charge critique de flambement de structures lattices. / The development of additive manufacturing allows structures with highly complex shapes to be produced. Complex lattice shapes are particularly interesting in the context of lightweight structures. However, although the use of this technology is growing in numerous engineering domains, this one is not enough matured and the correlations between the experimental data and deterministic simulations are not obvious. To take into account observed variations of behavior, multiparametric approaches are nowadays efficient solutions to tend to robust and reliable designs. The aim of this thesis is to integrate material and geometric uncertainty, experimentally quantified, in buckling analyses. To achieve this objective, different surrogate models, based on regression and correlation techniques as well as different reduced order models have been first evaluated to reduce the prohibitive computational time. The selected projections rely on modes calculated either from Proper Orthogonal Decomposition, from homotopy developments or from Taylor series expansion. Second, the proposed mathematical model is integrated in fuzzy and probabilistic analyses to estimate the evolution of the critical buckling load for lattice structures.

Master´s thesis deals about problematic of fuzzy logic, fuzzy sets and operation with them. Also thesis describing procedure of quantification risks through fuzzy sets, process of fuzzyfication, defuzzyfication a theirs application in the expert systems FMEA and FMECA. Using selected chapters of czech states standards are established critical areas in building process, it is a chapters about quality, safety and environment. With these areas by using fuzzy sets theory are created the procentual input values in the decision program, created by Matlab. Output from program is decision how big the risk rate is and if is necessarily make corrective measures. A concrete example is the production of concrete goods, describing production process and composition of fresh concrete. A practical example, created by using information from real company, is a decision about the risk rate in the qualitative area.

A fin de diseñar e implementar lenguajes de programación que tengan en cuenta el paradigma borroso modificaremos el lambda cálculo clásico, adjuntando a cada término un grado, y redefiniendo la beta-reducción, obteniendo que para que el nuevo cálculo verifique la propiedad de Church-Rosser la transmisión de los grados debe hacerse por medio de una función que sea una t-norma o s-conorma. Utilizando esta nueva herramienta diseñamos un lenguaje no determinista que satisface los requerimientos de la programación con datos borrosos. / With the aim of designing and implementing programming languages that take into account the fuzzy paradigm we will modify the classical lambda calculus by adding a degree to each term and by redefining the b-reduction. Thus, for the new calculus to verify the Church-Rosser property, the degree computed with can be made through a function that is a t-norm or an s-conorm. With this new tool we design a nondeterminist language that satisfies fuzzy dataprogramming requirements, and an example of its behaviour is shown.