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Related papers: On Ordered Fuzzy Numbers Generated By Time Series

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In this paper, the interval-valued intuitionistic fuzzy matrix (IVIFM) is introduced. The interval-valued intuitionistic fuzzy determinant is also defined. Some fundamental operations are also presented. The need of IVIFM is explain by an…

Discrete Mathematics · Computer Science 2014-04-29 Susanta Kumar Khan , Madhumangal Pal

We propose a new approach to temporal inference, inspired by the Pearlian causal inference paradigm - though quite different from Pearl's approach formally. Rather than using directed acyclic graphs, we make use of factored sets, which are…

Artificial Intelligence · Computer Science 2021-09-24 Scott Garrabrant

In mathematical modeling of the non-squared frequency-dependent diffusions, also known as the anomalous diffusions, it is desirable to have a positive real Fourier transform for the time derivative of arbitrary fractional or odd integer…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W Chen

Multivariate time series classification is a task with increasing importance due to the proliferation of new problems in various fields (economy, health, energy, transport, crops, etc.) where a large number of information sources are…

Machine Learning · Computer Science 2020-09-09 Francisco J. Baldán , José M. Benítez

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator $B$ which is specific in a plane is…

General Mathematics · Mathematics 2021-01-05 Yijin Zhang , Honggang Li , Maoming Jin , Zongbing Lin

Time series classification (TSC) is the problem of learning labels from time dependent data. One class of algorithms is derived from a bag of words approach. A window is run along a series, the subseries is shortened and discretised to form…

Machine Learning · Computer Science 2019-11-28 Anthony Bagnall , James Large , Matthew Middlehurst

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Despite a plethora of methods have been…

Physics and Society · Physics 2023-03-01 Andrea Santoro , Federico Battiston , Giovanni Petri , Enrico Amico

How to handle uncertainty in medical diagnosis is an open issue. In this paper, a new decision making methodology based on Z-numbers is presented. Firstly, the experts' opinions are represented by Z-numbers. Z-number is an ordered pair of…

Artificial Intelligence · Computer Science 2017-05-09 Dong Wu , Xiang Liu , Feng Xue , Hanqing Zheng , Yehang Shou , Wen Jiang

In this paper we propose a novel approach for learning from data using rule based fuzzy inference systems where the model parameters are estimated using Bayesian inference and Markov Chain Monte Carlo (MCMC) techniques. We show the…

Machine Learning · Statistics 2018-06-25 Indranil Pan , Dirk Bester

Admissible orders on fuzzy numbers are total orders which refine a basic and well-known partial order on fuzzy numbers. In this work, we define an admissible order on triangular fuzzy numbers (i.e. TFN's) and study some fundamental…

This paper investigates the generalized Hukuhara differentiability of fuzzy number-valued functions on arbitrary time scales using delta calculus. By carefully examining and improving existing results, we develop a unified and complete…

General Mathematics · Mathematics 2025-07-08 Funda Raziye Mert , Selami Bayeğ

Here a real life optimal control problem under fuzzy time period using variational principle is formulated and Solved. The unit production cost is a function of production rate and also dependent on raw material cost, development cost due…

Optimization and Control · Mathematics 2023-09-19 J. N. Roul , K. Maity , S. Kar , M. Maiti

The existence of large volumes of time series data in many applications has motivated data miners to investigate specialized methods for mining time series data. Clustering is a popular data mining method due to its powerful exploratory…

Machine Learning · Computer Science 2016-08-04 Fateme Fahiman , Jame C. Bezdek , Sarah M. Erfani , Christopher Leckie , Marimuthu Palaniswami

We present a new cycle flow based method for finding fuzzy partitions of weighted directed networks coming from time series data. We show that this method overcomes essential problems of most existing clustering approaches, which tend to…

Data Analysis, Statistics and Probability · Physics 2017-01-20 Ralf Banisch , Nataša Djurdjevac Conrad

This paper endeavors to learn time-varying graphs by using structured temporal priors that assume underlying relations between arbitrary two graphs in the graph sequence. Different from many existing chain structure based methods in which…

Machine Learning · Computer Science 2022-02-24 Xiang Zhang , Qiao Wang

In this paper we define fuzzy sequential topology on a non empty set X which is a collection of fuzzy sequential sets satisfying certain conditions given in its definition and many pleasant properties of a countable number of fuzzy…

General Topology · Mathematics 2012-09-27 M. Singha , N. Tamang , S. De Sarkar

Smoothing methods and SiZer are a useful statistical tool for discovering statistically significant structure in data. Based on scale space ideas originally developed in the computer vision literature, SiZer (SIgnificant ZERo crossing of…

Methodology · Statistics 2011-11-10 Vitaliana Rondonotti , J. S. Marron , Cheolwoo Park

The fractional order system, which is described by the fractional order derivative and integral, has been studied in many engineering areas. Recently, the concept of fractional order has been generalized to the distributed order concept,…

Systems and Control · Computer Science 2013-12-12 Pham Luu Trung Duong , Moonyong Lee

We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random…

Artificial Intelligence · Computer Science 2024-05-08 Thierry Denoeux

In this paper, we introduce a new type fuzzy boundary and study some related set theoretic identities. Further, this new type of fuzzy boundary is compared with different existing fuzzy boundaries.

General Mathematics · Mathematics 2012-08-13 J. Mahanta , P. K. Das
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