An agglomerative method for automatic forming of hierarchical classification
An Algorithmic Approach to Inferring Cross-Ontology Links while Mapping Anatomical Ontologies
ACM Computing Classification System (1998): J.3.Automated and semi-automated mapping and the subsequently merging of two (or more) anatomical ontologies can be achieved by (at least) two direct procedures. The first concerns syntactic matching between the terms of the two ontologies; in this paper, we call this direct matching (DM). It relies on identities between the terms of the two input ontologies in order to establish cross-ontology links between them. The second involves consulting one or...
An alternative approach to missing information in the GUHA method
An alternative approach to rough sets
An Application of Discriminant Analysis and Artificial Neural Networks to Classification Problems
An approach based on the use of the ant system to design combinational logic circuits.
In this paper we report the first attempt to design combinational logic circuits using the ant system. In order to design circuits, a measure of quality improvement in partially built circuits is introduced and a cost metric (based on the number of gates) is adopted in order to optimize the feasible circuits generated. The approach is compared to a genetic algorithm and to a human designer using several examples and the sensitivity of the algorithm to its parameters is studied using analysis of...
An Approach for Selecting Appropriate Methods for Treating Uncertainty in Knowledge Based Systems
An approach of the Naive Bayes classifier for the document classification.
An architecture for making judgments using computing with words
Our thesis is that computing with words needs to account for the uncertainties associated with the meanings of words, and that these uncertainties require using type-2 fuzzy sets. Doing this leads to a proposed architecture for making it judgments by means of computing with words, i.e., to a perceptual computer-the Per-C. The Per-C includes an encoder, a type-2 rule-based fuzzy logic system, and a decoder. It lets all human-computer interactions be performed using words. In this paper, a quantitative...
An attempt to formalize the notion of heuristics in state space
An automatic hybrid method for retinal blood vessel extraction
The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background information...
An axiom system for incidence spatial geometry.
Incidence spatial geometry is based on three-sorted structures consisting of points, lines and planes together with three intersort binary relations between points and lines, lines and planes and points and planes. We introduce an equivalent one-sorted geometrical structure, called incidence spatial frame, which is suitable for modal considerations. We are going to prove completeness by SD-Theorem. Extensions to projective, affine and hyperbolic geometries are also considered.
An effective global path planning algorithm with teaching-learning-based optimization
Due to the widespread use of mobile robots in various applications, the path planning problem has emerged as one of the important research topics. Path planning is defined as finding the shortest path starting from the initial point to the destination in such a way as to get rid of the obstacles it encounters. In this study, we propose a path planning algorithm based on a teaching-learning-based optimization (TLBO) algorithm with Bezier curves in a static environment with obstacles. The proposed...
An efficient algorithm for the maximum distance problem.
An efficient ART1 algorithm based on vector computation.
An Efficient Procedure for Mining Statistically Significant Frequent Itemsets
An efficient SQL-based querying method to RDF schemata
An evolutionary approach to constraint-regularized learning.
The success of machine learning methods for inducing models from data crucially depends on the proper incorporation of background knowledge about the model to be learned. The idea of constraint-regularized learning is to employ fuzzy set-based modeling techniques in order to express such knowledge in a flexible way, and to formalize it in terms of fuzzy constraints. Thus, background knowledge can be used to appropriately bias the learn ing process within the regularization framework of inductive...
An evolutionary approach to geometrical place problems.
An experimental evaluation of two approaches to mining context based sequential patterns