A data model architecture for parametrics.
A data model for indexing and searching XML documents.
A database model for library material usage.
A decision method for the recognizability of sets defined by number systems
A decision support system for regional hazardous waste management alternatives.
A decomposition and noise removal method combining diffusion equation and wave atoms for textured images.
A deductive calculus for conditional equational systems with built-in predicates as premises.
A defuzzification based new algorithm for the design of Mamdani-type fuzzy controllers
This paper presents a new learning algorithm for the design of Mamdani- type or fully-linguistic fuzzy controllers based on available input-output data. It relies on the use of a previously introduced parametrized defuzzification strategy. The learning scheme is supported by an investigated property of the defuzzification method. In addition, the algorithm is tested by considering a typical non-linear function that has been adopted in a number of published research articles. The test stresses on...
A density version of the Carlson–Simpson theorem
We prove a density version of the Carlson–Simpson Theorem. Specifically we show the following. For every integer and every set of words over satisfying there exist a word over and a sequence of left variable words over such that the set is contained in . While the result is infinite-dimensional its proof is based on an appropriate finite and quantitative version, also obtained in the paper.
A deterministic subclass of context-free languages
A differential evolution approach to dimensionality reduction for classification needs
A direct decomposition of 3-connected planar graphs.
A Discrete Wavelet Transform Without Edge Effects Using Wavelet Extrapolation.
A discrete-time software reliability-growth model and its application for predicting the number of errors encountered during program testing
A discussion on aggregation operators
It has been lately made very clear that aggregation processes can not be based upon a unique binary operator. Global aggregation operators have been therefore introduced as families of aggregation operators , being each one of these the -ary operator actually amalgamating information whenever the number of items to be aggregated is . Of course, some mathematical restrictions can be introduced, in order to assure an appropriate meaning, consistency and key mathematical capabilities. In this...
A Distance-Based Method for Attribute Reduction in Incomplete Decision Systems
There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods.
A distributed transportation simplex applied to a Content Distribution Network problem
A Content Distribution Network (CDN) can be defined as an overlay system that replicates copies of contents at multiple points of a network, close to the final users, with the objective of improving data access. CDN technology is widely used for the distribution of large-sized contents, like in video streaming. In this paper we address the problem of finding the best server for each customer request in CDNs, in order to minimize the overall cost. We consider the problem as a transportation problem...
A distributed voting scheme to maximize preferences
We study the problem of designing a distributed voting scheme for electing a candidate that maximizes the preferences of a set of agents. We assume the preference of agent i for candidate j is a real number xi,j, and we do not make any assumptions on the mechanism generating these preferences. We show simple randomized voting schemes guaranteeing the election of a candidate whose expected total preference is nearly the highest among all candidates. The algorithms we consider are designed so that...
A Divide and Conquer Method for the Symmetric Tridiagonal Eigenproblem.
A dynamic model of classifier competence based on the local fuzzy confusion matrix and the random reference classifier
Nowadays, multiclassifier systems (MCSs) are being widely applied in various machine learning problems and in many different domains. Over the last two decades, a variety of ensemble systems have been developed, but there is still room for improvement. This paper focuses on developing competence and interclass cross-competence measures which can be applied as a method for classifiers combination. The cross-competence measure allows an ensemble to harness pieces of information obtained from incompetent...