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A New Hybrid Model of Fuzzy Time Series and Genetic Algorithm Based Machine Learning Algorithm: A Case Study of Forecasting Prices of Nine Types of Major Cryptocurrencies

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.20145openalex-snapshot
Forecasting enrollments using high-order fuzzy time series and genetic algorithms
inferredcites →https://doi.org/10.1007/s10489-014-0529-xopenalex-snapshot
A modified genetic algorithm for forecasting fuzzy time series
inferredcites →https://doi.org/10.1007/s10700-018-9290-7openalex-snapshot
An improved fuzzy time series forecasting model using variations of data
inferredcites →https://doi.org/10.1016/0165-0114(93)90355-lopenalex-snapshot
Forecasting enrollments with fuzzy time series — Part I
inferredcites →https://doi.org/10.1016/0165-0114(93)90372-oopenalex-snapshot
Fuzzy time series and its models
inferredcites →https://doi.org/10.1016/0165-0114(94)90067-1openalex-snapshot
Forecasting enrollments with fuzzy time series — part II
inferredcites →https://doi.org/10.1016/0165-0114(95)00220-0openalex-snapshot
Forecasting enrollments based on fuzzy time series
inferredcites →https://doi.org/10.1016/j.amc.2006.07.128openalex-snapshot
A simple method of forecasting based on fuzzy time series
inferredcites →https://doi.org/10.1016/j.asoc.2014.03.028openalex-snapshot
Fuzzy lagged variable selection in fuzzy time series with genetic algorithms
inferredcites →https://doi.org/10.1016/j.asoc.2017.01.043openalex-snapshot
A novel high-order weighted fuzzy time series model and its application in nonlinear time series prediction
inferredcites →https://doi.org/10.1016/j.ejor.2019.01.040openalex-snapshot
Bitcoin price forecasting with neuro-fuzzy techniques
inferredcites →https://doi.org/10.1016/j.eswa.2009.02.061openalex-snapshot
A computational method of forecasting based on high-order fuzzy time series
inferredcites →https://doi.org/10.1016/j.frl.2018.09.014openalex-snapshot
Bitcoin returns and risk: A general GARCH and GAS analysis
inferredcites →https://doi.org/10.1016/j.jfds.2018.10.001openalex-snapshot
Predicting bitcoin returns using high-dimensional technical indicators
inferredcites →https://doi.org/10.1016/j.jocs.2018.05.008openalex-snapshot
A hybrid fuzzy time series forecasting model based on granular computing and bio-inspired optimization approaches
inferredcites →https://doi.org/10.1016/j.matcom.2008.02.026openalex-snapshot
A computational method of forecasting based on fuzzy time series
inferredcites →https://doi.org/10.1016/j.najef.2019.03.019openalex-snapshot
Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches
inferredcites →https://doi.org/10.1016/j.procs.2013.05.281openalex-snapshot
A Novel Stock Forecasting Model based on Fuzzy Time Series and Genetic Algorithm
inferredcites →https://doi.org/10.1016/j.procs.2018.05.050openalex-snapshot
NSE Stock Market Prediction Using Deep-Learning Models
inferredcites →https://doi.org/10.1016/s0165-0114(00)00093-2openalex-snapshot
Heuristic models of fuzzy time series for forecasting
inferredcites →https://doi.org/10.1037/h0042519openalex-snapshot
The perceptron: A probabilistic model for information storage and organization in the brain.
inferredcites →https://doi.org/10.1063/1.5008700openalex-snapshot
Real coded genetic algorithm for fuzzy time series prediction
inferredcites →https://doi.org/10.1080/019697202753306479openalex-snapshot
FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES
inferredcites →https://doi.org/10.1088/1742-6596/1053/1/012005openalex-snapshot
Foreign exchange rates forecasting with an EMD-LSTM neural networks model
inferredcites →https://doi.org/10.1108/imds-05-2015-0165openalex-snapshot
Genetic algorithm based fuzzy time series tourism demand forecast model
inferredcites →https://doi.org/10.1109/21.256541openalex-snapshot
ANFIS: adaptive-network-based fuzzy inference system
inferredcites →https://doi.org/10.1109/icmla.2018.00227openalex-snapshot
A Comparison of ARIMA and LSTM in Forecasting Time Series
inferredcites →https://doi.org/10.1109/tsmcb.2010.2042055openalex-snapshot
Adaptive Time-Variant Models for Fuzzy-Time-Series Forecasting
inferredcites →https://doi.org/10.1142/s1469026818500190openalex-snapshot
A New High-Order Approach for Forecasting Fuzzy Time Series Data
inferredcites →https://doi.org/10.1142/s1793962312500237openalex-snapshot
A COMPUTATIONAL METHOD FOR FUZZY TIME SERIES FORECASTING BASED ON DIFFERENCE PARAMETERS
inferredcites →https://doi.org/10.11591/eei.v7i3.1181openalex-snapshot
Weather Forecasting Using Merged Long Short-term Memory Model
inferredcites →https://doi.org/10.13140/rg.2.1.4539.5281openalex-snapshot
Forecast Error Measures: Critical Review and Practical Recommendations
inferredcites →https://doi.org/10.13140/rg.2.2.15847.57766openalex-snapshot
Predicting bitcoin price using lstm And Compare its predictability with arima model 1
inferredcites →https://doi.org/10.1371/journal.pone.0209922openalex-snapshot
Forecasting leading industry stock prices based on a hybrid time-series forecast model
inferredcites →https://doi.org/10.22161/ijaers.4.11.20openalex-snapshot
Autoregressive Integrated Moving Average (ARIMA) Model for Forecasting Cryptocurrency Exchange Rate in High Volatility Environment: A New Insight of Bitcoin Transaction
inferredcites →https://doi.org/10.22457/ijfma.v13n2a5openalex-snapshot
A Computational Method for Rice Production Forecasting Based on High-Order Fuzzy Time Series
inferredcites →https://doi.org/10.23919/icact.2018.8323675openalex-snapshot
Bitcoin price prediction using machine learning
inferredcites →https://doi.org/10.23919/icact.2018.8323676openalex-snapshot
Bitcoin price prediction using machine learning
inferredcites →https://doi.org/10.2478/cait-2018-0001openalex-snapshot
A Unique Computational Method for Constructing Intervals in Fuzzy Time Series Forecasting
inferredcites →https://doi.org/10.32890/jict2016.15.2.8openalex-snapshot
Deseasonalised Forecasting Model of Rainfall Distribution Using Fuzzy Time Series
inferredcites →https://doi.org/10.3390/data4020075openalex-snapshot
A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine
inferredcites →https://doi.org/10.3390/jrfm11040063openalex-snapshot
An Analysis of Bitcoin’s Price Dynamics
inferredcites →https://doi.org/10.3390/jrfm12020103openalex-snapshot
Next-Day Bitcoin Price Forecast
inferredcites →https://doi.org/10.3390/w10111543openalex-snapshot
Deep Learning with a Long Short-Term Memory Networks Approach for Rainfall-Runoff Simulation
inferredcites →https://doi.org/10.7717/peerj-cs.279openalex-snapshot
Forecasting Bitcoin closing price series using linear regression and neural networks models

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4663472openalex-extracted
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inferred← citeshttps://doi.org/10.1007/s12065-025-01078-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44443-025-00045-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44443-026-00551-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bdr.2024.100455openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bdr.2026.100627openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.egyr.2023.08.039openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.nexres.2026.101513openalex-snapshot
Review of deep learning models for crypto price prediction: Implementation and evaluation
inferred← citeshttps://doi.org/10.1080/02533839.2025.2517349openalex-snapshot
Battery state of charge estimation for electric vehicle based on hybrid barnacles mating optimizer-feed forward neural network
inferred← citeshttps://doi.org/10.1108/cfri-03-2023-0072openalex-snapshot
A novel granular decomposition based predictive modeling framework for cryptocurrencies' prices forecasting
inferred← citeshttps://doi.org/10.1109/iccce58854.2023.10246100openalex-snapshot
Measurement and forecasting of fluctuating Cryptocurrency prices using deep learning
inferred← citeshttps://doi.org/10.1109/icics60529.2023.10330473openalex-snapshot
Testing Lasso Regression and XGBOOST on Crypto-Currency Volatility and Price Prediction
inferred← citeshttps://doi.org/10.1145/3788149.3788168openalex-snapshot
Cryptocurrency Price Prediction using a Hybrid Deep Learning Approach with Explainable AI Integration
inferred← citeshttps://doi.org/10.11591/ijece.v13i6.pp7016-7026openalex-snapshot
Best-worst northern goshawk optimizer: a new stochastic optimization method
inferred← citeshttps://doi.org/10.3390/biomimetics8030278openalex-snapshot
A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics
inferred← citeshttps://doi.org/10.34110/forecasting.2004084openalex-snapshot
A Comparative Performance Analysis of Artificial Bee Colony, Genetic Algorithm, Particle Swarm Optimization, and Sine Cosine Algorithm for Training a Robust Cauchy-Huber Dendritic Neuron Model in Bitcoin Log-Return Forecasting
inferred← citeshttps://doi.org/10.62527/joiv.8.1.1543openalex-snapshot
Minimum, Maximum, and Average Implementation of Patterned Datasets in Mapping Cryptocurrency Fluctuation Patterns
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