À propos de l’optimalité des algorithmes numériques : étude du calcul de
A Prototype of an Extension to the UDDI Registry Allowing Pubilcation and Search Based on Subjective Evaluations
The paper has been presented at the International Conference Pioneers of Bulgarian Mathematics, Dedicated to Nikola Obreshko and Lubomir Tschakalo , So a, July, 2006.The current paper introduces the usage of subjective evaluations by others as a tool that can support consumers' decisions. It summarizes the features of the main UDDI registry providers and presents an extension to any UDDI registry allowing users of the registry to publish subjective evaluations for any artifact found in it and to...
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 qualitative trajectory calculus as a basis for representing moving objects in Geographical Information Systems
A queueing model for error control of partial buffer sharing in ATM.
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...
A real-time identification of continuous linear systems
A Reconstruction of Digital Parabolas from Their Least Squares Fit Representation
A Recursive Algorithm for the Maximum Cardinality Independent set
A RED modified weighted moving average for soft real-time application
The popularity of TCP/IP has resulted in an increase in usage of best-effort networks for real-time communication. Much effort has been spent to ensure quality of service for soft real-time traffic over IP networks. The Internet Engineering Task Force has proposed some architecture components, such as Active Queue Management (AQM). The paper investigates the influence of the weighted moving average on packet waiting time reduction for an AQM mechanism: the RED algorithm. The proposed method for...
A reduction-based theorem prover for 3-valued logic.
We present a new prover for propositional 3-valued logics, TAS-M3, which is an extension of the TAS-D prover for classical propositional logic. TAS-M3 uses the TAS methodology and, consequently, it is a reduction-based method. Thus, its power is based on the reductions of the size of the formula executed by the F transformation. This transformation dynamically filters the information contained in the syntactic structure of the formula to avoid as much distributions as possible, in order to improve...
A reformulation of matrix graph grammars with Boolean complexes.
A reliable method to determine the ill-condition functions using stochastic arithmetic.
A remark on morphic sturmian words
A Revision about the Concept of Intentionality in an Approximate Framework.
A ring to describe symbolic expressions.
A rough set-based knowledge discovery process
The knowledge discovery from real-life databases is a multi-phase process consisting of numerous steps, including attribute selection, discretization of real-valued attributes, and rule induction. In the paper, we discuss a rule discovery process that is based on rough set theory. The core of the process is a soft hybrid induction system called the Generalized Distribution Table and Rough Set System (GDT-RS) for discovering classification rules from databases with uncertain and incomplete data....
A rule based machine learning approach to the nonlinear multifingered robot gripper problem
A scaling result for explosive processes.