Fuzzy XPath for the Automatic Search of Fuzzy Formulae Models
نویسندگان
چکیده
In this paper we deal with propositional fuzzy formulae containing several propositional symbols linked with connectives defined in a lattice of truth degrees more complex than Bool. Instead of focusing on satisfiability (i.e., proving the existence of at least one model) as usually done in a SAT/SMT setting, our interest moves to the problem of finding the whole set of models (with a finite domain) for a given fuzzy formula. We re-use a previous method based on fuzzy logic programming where the formula is conceived as a goal whose derivation tree, provided by our FLOPER tool, contains on its leaves all the models of the original formula, together with other interpretations. Next, we use the ability of the FuzzyXPath tool (developed in our research group with FLOPER) for exploring these derivation trees once exported in XML format, in order to discover whether the formula is a tautology, satisfiable, or a contradiction, thus reinforcing the bi-lateral synergies between FuzzyXPath and FLOPER.
منابع مشابه
Automatic Calibration of HEC-HMS Model Using Multi-Objective Fuzzy Optimal Models
Estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. This study aimed to use the particle swarm optimization (PSO) algorithm for automatic calibration of the HEC-HMS hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...
متن کاملFuzzy XPath Queries in XQuery
We have recently designed a fuzzy extension of the XPath language which provides ranked answers to flexible queries taking profit of fuzzy variants of and, or and avg operators for XPath conditions, as well as two structural constraints, called down and deep, for which a certain degree of relevance is associated. In this work, we describe how to implement the proposed fuzzy XPath with the XQuer...
متن کاملSECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS
In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...
متن کاملFuzzy Neighbor Voting for Automatic Image Annotation
With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...
متن کاملPrediction of toxicity of aliphatic carboxylic acids using adaptive neuro-fuzzy inference system
Toxicity of 38 aliphatic carboxylic acids was studied using non-linear quantitative structure-toxicityrelationship (QSTR) models. The adaptive neuro-fuzzy inference system (ANFIS) was used to construct thenonlinear QSTR models in all stages of study. Two ANFIS models were developed based upon differentsubsets of descriptors. The first one used log ow K and LUMO E as inputs and had good predicti...
متن کامل