A new heuristic algorithm of fuzzy clustering
A new high-speed foreign fiber detection system with machine vision.
A new method based on least-squares support vector regression for solving optimal control problems
In this paper, a new application of the Least Squares Support Vector Regression (LS-SVR) with Legendre basis functions as mapping functions to a higher dimensional future space is considered for solving optimal control problems. At the final stage of LS-SVR, an optimization problem is formulated and solved using Maple optimization packages. The accuracy of the method are illustrated through numerical examples, including nonlinear optimal control problems. The results demonstrate that the proposed...
A new model of combinatorial probability
A new possibility in bi-directional search
A new search model for evolutionary algorithms.
A new uncertainty-aware similarity for user-based collaborative filtering
User-based Collaborative Filtering (UBCF) is a common approach in Recommender Systems (RS). Essentially, UBCF predicts unprovided entries for the target user by selecting similar neighbors. The effectiveness of UBCF greatly depends on the selected similarity measure and the subsequent choice of neighbors. This paper presents a new Uncertainty-Aware Similarity measure "UASim" which enhances CF by accurately calculating how similar, dissimilar, and uncertain users' preferences are. Uncertainty is...
A new variational model for segmenting objects of interest from color images.
A Noetherian and confluent rewrite system for idempotent semigroups.
A nonstandard modification of Dempster combination rule
It is a well-known fact that the Dempster combination rule for combination of uncertainty degrees coming from two or more sources is legitimate only if the combined empirical data, charged with uncertainty and taken as random variables, are statistically (stochastically) independent. We shall prove, however, that for a particular but large enough class of probability measures, an analogy of Dempster combination rule, preserving its extensional character but using some nonstandard and boolean-like...
A note on -algebras.
A note on fixpoint techniques in data base recursive logic programs
A note on the computational complexity of hierarchical overlapping clustering
In this paper the computational complexity of the problem of the approximation of a given dissimilarity measure on a finite set by a -ultrametric on and by a Robinson dissimilarity measure on is investigared. It is shown that the underlying decision problems are NP-complete.
A note on the richness of convex hulls of VC classes.
A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems
A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization...
A novel medical diagnosis system.
A primal sub-gradient method for structured classification with the averaged sum loss
A probabilistic approach to automaton-environment systems
A PROLOG program for analysis and synthesis of typical sentences taken from advertisements
A proximity based macro stress testing framework
In this a paper a non-linear macro stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It is embedded in a framework, in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset, allowing to estimate a stressed future state. It will be shown that contagion can be directly derived from the proximities while...