Using automated reasoning tools: A study of the semigroup F2B2.
Using fuzzy similarity relations to revise and update a knowledge base.
Similarity-based models were first used by Ruspini to give semantics to fuzzy logic. In these models, incomplete information is represented by an evidential set, i.e. a set of possible worlds that are compatible with the evidence, together with a fuzzy similarity relation} on the set of possible worlds that allows to describe the resemblance of arbitrary subsets of worlds to those belonging to the evidencial set. On the other hand, the question addressed by theory change formalisms is which kind...
Using genetic feature selection for optimizing user profiles.
Most of the techniques used in text classification are determined by the occurrences of the words (terms) appearing in the documents, combined with the user feedback over the documents retrieved. However, in our model, the most relevant terms will be selected from a previous fuzzy classification given by the genetic algorithm guided by the user feedback, but using techniques from Machine Learning. A feature selection process is carried out through a Genetic Algorithm in order to find the most discriminatory...
Using the possibility theory in fuzzy temporal reasoning
Vagueness and its representations: a unifying look.
Using the notion of a vaguely defined object, we systematize and unify different existing approaches to vagueness and its mathematical representations, including fuzzy sets and derived concepts. Moreover, a new, approximative approach to vaguely defined objects will be introduced and investigated.
Variational Gaussian process for optimal sensor placement
Sensor placement is an optimisation problem that has recently gained great relevance. In order to achieve accurate online updates of a predictive model, sensors are used to provide observations. When sensor location is optimally selected, the predictive model can greatly reduce its internal errors. A greedy-selection algorithm is used for locating these optimal spatial locations from a numerical embedded space. A novel architecture for solving this big data problem is proposed, relying on a variational...
Variations on undirected graphical models and their relationships
We compare alternative definitions of undirected graphical models for discrete, finite variables. Lauritzen [7] provides several definitions of such models and describes their relationships. He shows that the definitions agree only when joint distributions represented by the models are limited to strictly positive distributions. Heckerman et al. [6], in their paper on dependency networks, describe another definition of undirected graphical models for strictly positive distributions. They show that...
Veblen Hierarchy
The Veblen hierarchy is an extension of the construction of epsilon numbers (fixpoints of the exponential map: ωε = ε). It is a collection φα of the Veblen Functions where φ0(β) = ωβ and φ1(β) = εβ. The sequence of fixpoints of φ1 function form φ2, etc. For a limit non empty ordinal λ the function φλ is the sequence of common fixpoints of all functions φα where α < λ.The Mizar formalization of the concept cannot be done directly as the Veblen functions are classes (not (small) sets). It is done...
Verification of the Formal Concept Analysis.
This paper is concerned with a formal verification of the Formal Concept Analysis framework. We use the PVS system to represent and formally verify some algorithms of this theory. We also develop a method to transform specifications of algorithms based on finite sets into other executable ones, preserving its correctness. We illustrate this method by constructing an executable algorithm to compute an implicational base of the system of implications between attributes of a finite formal context.
Virtual enterprise risk management using artificial intelligence.
Visione delle macchine: una sfida anche per i matematici
Visual anomaly detection via soft computing: a prototype application at NASA.
A visual system prototype that detects anomalies or defects in real time under normal lighting operating conditions was built for NASA at the Kennedy Space Center (KSC). The system prototype is basically a learning machine that integrates the three elements of soft computing, Fuzzy Logic (FL), Artificial Neural Network (ANN), and Genetic Algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation...
Visual measurement of suture strain for robotic surgery.
Web-strabnet: a web-based expert system for the differential diagnosis of vertical strabismus (squint).
Weighting quantitative and qualitative variables in clustering methods.
Description of individuals in ill-structured domains produces messy data matrices. In this context, automated classification requires the management of those kind of matrices. One of the features involved in clustering is the evaluation of distances between individuals. Then, a special function to calculate distances between individuals partially simultaneously described by qualitative and quantitative variables is required.In this paper properties and details of the metrics used by Klass in this...
What machines can and cannot do.
In this paper, the questions of what machines cannot do and what they can do will be treated by examining the ideas and results of eminent mathematicians. Regarding the question of what machines cannot do, we will rely on the results obtained by the mathematicians Alan Turing and Kurt G¨odel. Turing machines, their purpose of defining an exact definition of computation and the relevance of Church-Turing thesis in the theory of computability will be treated in detail. The undecidability of the “Entscheidungsproblem”...
Wildfires identification: Semantic segmentation using support vector machine classifier
This paper deals with wildfire identification in the Alaska regions as a semantic segmentation task using support vector machine classifiers. Instead of colour information represented by means of BGR channels, we proceed with a normalized reflectance over 152 days so that such time series is assigned to each pixel. We compare models associated with -loss and -loss functions and stopping criteria based on a projected gradient and duality gap in the presented benchmarks.
Yager’s classes of fuzzy implications: some properties and intersections
Recently, Yager in the article “On some new classes of implication operators and their role in approximate reasoning” [Yager2004] has introduced two new classes of fuzzy implications called the -generated and -generated implications. Along similar lines, one of us has proposed another class of fuzzy implications called the -generated implications. In this article we discuss in detail some properties of the above mentioned classes of fuzzy implications and we describe their relationships amongst...
Z specification of object oriented constraint programs.
Object oriented constraint programs (OOCPs) emerge as a leading evolution of constraint programming and artificial intelligence, first applied to a range of industrial applications called configuration problems. The rich variety of technical approaches to solving configuration problems (CLP(FD), CC(FD), DCSP, Terminological systems, constraint programs with set variables, . . . ) is a source of difficulty. No universally accepted formal language exists for communicating about OOCPs, which makes...
Алгебраическое исследование простейших кодов и бсекоэффициентных уравнений в словах