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304 915 (0,272s)

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Quantum Approach into Probabilistic Binary Modeling

The paper presents the theory of wave probabilistic models together with their important features like inclusion-exclusion rule, product rule, complementary principle and entanglement. These features are mathematically described and...

BD - Teorie informace

  • 2009
  • D
Result

Quasi-Non-Ergodic Probabilistic Systems and Wave Probabilistic Functions

This paper presents models of quasi-non-ergodic probabilistic systems that are defined through the theory of wave probabilistic functions presented in [10-16]. First of all we show the new methodology oil a binary non-ergod...

BD - Teorie informace

  • 2009
  • Jx
Result

Fuzzy vs. Probabilistic Techniques in Time Series Analysis

of time series and what is their outcome in comparison with the probabilisticIn this paper, we discuss the difference between probabilistic and fuzzy techniques used in time series analysis. Firs...

Statistics and probability

  • 2018
  • D
  • Link
Result

Wave Probabilistic Models

The paper presents the basic theory of wave probabilistic models together with their features. By introduction of complementarity's principle between x-representation and k information about the changes of time series

JO - Pozemní dopravní systémy a zařízení

  • 2007
  • Jx
Result

Complementary variables and its application in statistics

application in the area of applied probabilistic modeling. By introduction of complementarity's principle between x-representation (random time series, random process) and p-representation or k-representation (rat...

JO - Pozemní dopravní systémy a zařízení

  • 2007
  • Jx
Result

RE-SAMPLING ESTIMATION IN TIME SERIES

Many probabilistic models are used to analyse the time series. Two different methods for bootstrapping time series are described in the paper. The simplest model to the original time<...

BB - Aplikovaná statistika, operační výzkum

  • 2007
  • D
Result

Tensor Rank-One Decomposition of Probability Tables

the space and time requirements in probabilistic inference. Weprovide a closed form decomposition. The basic idea is to decompose a probability table into a series of tables, such that the table that is the sum of the ...

BA - Obecná matematika

  • 2006
  • D
Result

RBF Neural Network Implementation of Fuzzy Systems: Application to Time Series Modeling

by the soft concept. Time series approximation and prediction by applying RBF neural networks or fuzzy models and comparisons between the various types of RBF networks and statistical models are discussed at lengt...

AH - Ekonomie

  • 2007
  • D
Result

Technical documentation of the TIMES model extended with demand parameters, emission coefficients and TCO module

The technical documentation describes in 3 chapters the development process of the TIMES model. The introductory chapter 1 presents the structure of the TIMES model of vehicles from the fleet based on a time

Environmental sciences (social aspects to be 5.7)

  • 2022
  • O
Result

Comparison of approximation and forecastig ability of various RBF NNW models with statisstical models

powerful fuzzy modeling technique. Then, the similarity between RBF networks and fuzzy models is noted in detail. Then, we propose the extension of RBF neural networks by the cloud model. Time series appr...

AH - Ekonomie

  • 2007
  • D
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