Mixed order single variable intuitionistic fuzzy time series forecasting method based on a new artificial neural network and grey wolf optimization algorithm [PDF]
Scientific ReportsThe ease of use of fuzzy time series methods and their success in forecasting performance have led to a rapid increase in research in this field. While classical fuzzy time series methods operate solely on membership values, intuitionistic fuzzy time ...
Turan Cansu, Eren Bas, Erol Egrioglu
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Adaptive Non-Stationary Fuzzy Time Series Forecasting with Bayesian Networks [PDF]
SensorsDespite its interpretability and excellence in time series forecasting, the fuzzy time series forecasting model (FTSFM) faces significant challenges when handling non-stationary time series.
Bo Wang, Xiaodong Liu
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Multilayer Stock Forecasting Model Using Fuzzy Time Series [PDF]
The Scientific World Journal, 2014 After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings.
Hossein Javedani Sadaei +1 more
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Evolving single- and multi-model fuzzy classifiers with FLEXFIS-class [PDF]
, 2007 [2] R. Santos, E. Dougherty, and J. A. Jaakko, “Creating fuzzy rules for image classification using biased data clustering,” in SPIE proceedings series (SPIE proc. ser.) International Society for Optical Engineering proceedings series.
Angelov, Plamen +5 more
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On-line evolution of Takagi-Sugeno fuzzy models [PDF]
, 2004 Evolving Takagi-Sugeno (eTS) fuzzy models and the method for their on-line identification has been recently introduced for both MISO and MIMO case. In this paper, the mechanism for rule-base evolution, one of the central points of the algorithm together ...
Angelov, Plamen +7 more
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Real-Time joint Landmark Recognition and Classifier Generation by an Evolving Fuzzy System. [PDF]
, 2006 A new approach to real-time joint classification and classifier design is proposed in this paper. It is based on the recently developed evolving fuzzy system (EFS) method and is applied to mobile robotics.
Angelov, Plamen +3 more
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Classification of Stabilometric Time-Series Using an Adaptive Fuzzy Inference Neural Network System [PDF]
, 2010 Stabilometry is a branch of medicine that studies balance-related human functions. The analysis of stabilometric-generated time series can be very useful to the diagnosis and treatment balance-related dysfunctions such as dizziness.
Caraça-Valente Hernández, Juan Pedro +9 more
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E-Jurnal Matematika, 2023 Forecasting is a way to predict future events. One of the methods for forecasting is to use fuzzy time series Chen method. Fuzzy time series Chen is a development of fuzzy time series Song and Chissom method with more simplified arithmetic operations. In
ULYATIL AENI +2 more
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A FUZZY TIME SERIES-MARKOV CHAIN MODEL TO FORECAST FISH FARMING PRODUCT
Jurnal Ilmiah Kursor: Menuju Solusi Teknologi Informasi, 2018 Price is one of the important things that need to concern as defining factor of the profit or loss of product selling as the result of price fluctuations that are very difficult to control. Price fluctuations are caused by many factors including weather,
Bagus Dwi Saputra +2 more
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Fuzzy Supervised Multi-Period Time Series Forecasting
Cybernetics and Information Technologies, 2019 The goal of this paper is to propose a new method for fuzzy forecasting of time series with supervised learning and k-order fuzzy relationships. In the training phase based on k previous historical periods, a multidimensional matrix of fuzzy dependencies
Ilieva Galina
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