A new heuristic algorithm of fuzzy clustering
A new high-speed foreign fiber detection system with machine vision.
A new model of combinatorial probability
A new possibility in bi-directional search
A new search model for evolutionary algorithms.
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...
A queueing problem in pattern recognition
A rainfall forecasting method using machine learning models and its application to the Fukuoka city case
In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid multi-model...