Using empirical wavelet transform and high-order fuzzy cognitive maps for time series forecasting
HA Mohammadi, S Ghofrani, A Nikseresht - Applied Soft Computing, 2023 - Elsevier
Many studies on time series forecasting have employed fuzzy cognitive maps (FCMs).
However, it is required to develop techniques capable of effective responses and great …
However, it is required to develop techniques capable of effective responses and great …
A novel wind speed forecasting combined model using variational mode decomposition, sparse auto-encoder and optimized fuzzy cognitive mapping network
Y Hu, Y Guo, R Fu - Energy, 2023 - Elsevier
The nonlinear, random and fluctuating characteristics of wind speed bring great challenges
to its accurate forecast, so no model that can adapt to all situations. In order to solve the …
to its accurate forecast, so no model that can adapt to all situations. In order to solve the …
Time-series forecasting based on high-order fuzzy cognitive maps and wavelet transform
S Yang, J Liu - IEEE Transactions on Fuzzy Systems, 2018 - ieeexplore.ieee.org
Fuzzy cognitive maps (FCMs) have been successfully used to model and predict stationary
time series. However, it still remains challenging to deal with large-scale nonstationary time …
time series. However, it still remains challenging to deal with large-scale nonstationary time …
Time series prediction using sparse autoencoder and high-order fuzzy cognitive maps
The problem of time series prediction based on fuzzy cognitive maps (FCMs) is unresolved.
Although many methods have been proposed to cope with this issue, the performance of …
Although many methods have been proposed to cope with this issue, the performance of …
A hesitant approach to sustainable supply chain risk assessment
Supply chains (SCs) are increasingly vulnerable to disruptive events, posing risks to all
involved parties. Managing and mitigating these risks is crucial for resilient and sustainable …
involved parties. Managing and mitigating these risks is crucial for resilient and sustainable …
Broad fuzzy cognitive map systems for time series classification
Time series classification (TSC) is a crucial and challenging problem in sequential analysis.
However, most of the existing best-performing methods are time-consuming, even if coping …
However, most of the existing best-performing methods are time-consuming, even if coping …
Uncertainty propagation in fuzzy grey cognitive maps with Hebbian-like learning algorithms
JL Salmeron, PR Palos-Sanchez - IEEE transactions on …, 2017 - ieeexplore.ieee.org
This paper is focused on an innovative fuzzy cognitive maps extension called fuzzy grey
cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems …
cognitive maps (FGCMs). FGCMs are a mixture of fuzzy cognitive maps and grey systems …
Learning large-scale fuzzy cognitive maps using an evolutionary many-task algorithm
Fuzzy cognitive maps (FCMs) are a powerful tool for simulating and analyzing complex
systems. Many efficient methods based on evolutionary algorithms have been proposed to …
systems. Many efficient methods based on evolutionary algorithms have been proposed to …
Strategizing sustainability in the banking industry using fuzzy cognitive maps and system dynamics
BMR Paiva, FAF Ferreira, EG Carayannis… - … Development & World …, 2021 - Taylor & Francis
Sustainable banking is an issue that has been growing in importance around the world
since the 2008 global crisis. Because the banking system is a major economic and financial …
since the 2008 global crisis. Because the banking system is a major economic and financial …
A framework of fermatean fuzzy cognitive map and its extension based on Hamacher operation
L Sha, Y Shao, Y Li - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Fuzzy cognitive map (FCM) has gained considerable attention for their efficacy in
addressing uncertainty reasoning problems, prompting extensive research and …
addressing uncertainty reasoning problems, prompting extensive research and …