A brief review of modeling approaches based on fuzzy time series

P Singh - International Journal of Machine Learning and …, 2017‏ - Springer
Recently, there seems to be increased interest in time series forecasting using soft
computing (SC) techniques, such as fuzzy sets, artificial neural networks (ANNs), rough set …

Develo** a deep learning framework with two-stage feature selection for multivariate financial time series forecasting

T Niu, J Wang, H Lu, W Yang, P Du - Expert Systems with Applications, 2020‏ - Elsevier
Intelligent financial forecasting modeling plays an important role in facilitating investment-
related decision-making activities in financial markets. However, accurate multivariate …

[HTML][HTML] Designing fuzzy time series forecasting models: A survey

M Bose, K Mali - International Journal of Approximate Reasoning, 2019‏ - Elsevier
Time Series is an orderly sequence of values of a variable in a particular domain.
Forecasting is a challenging task in the area of Time Series Analysis. Forecasting has a …

[PDF][PDF] A tutorial on fuzzy time series forecasting models: recent advances and challenges

PO Lucas, O Orang, PCL Silva, EM Mendes… - Learn Nonlinear …, 2022‏ - researchgate.net
Time series forecasting is a powerful tool in planning and decision making, from traditional
statistical models to soft computing and artificial intelligence approaches several methods …

Predictive intelligence using ANFIS‐induced OWAWA for complex stock market prediction

W Hussain, JM Merigó, MR Raza - International Journal of …, 2022‏ - Wiley Online Library
Traditional time series prediction methods are unable to handle the complex nonlinear
relationship of a large data set. Most of the existing techniques are unable to manage …

Fuzzy time series forecasting with a novel hybrid approach combining fuzzy c-means and neural networks

E Egrioglu, CH Aladag, U Yolcu - Expert Systems with Applications, 2013‏ - Elsevier
In recent years, time series forecasting studies in which fuzzy time series approach is utilized
have got more attentions. Various soft computing techniques such as fuzzy clustering …

A novel forecasting method based on multi-order fuzzy time series and technical analysis

F Ye, L Zhang, D Zhang, H Fujita, Z Gong - Information Sciences, 2016‏ - Elsevier
Financial trading is one of the most common risk investment actions in the modern economic
environment because financial market systems are complex non-linear dynamic systems. It …

Forecasting in non-stationary environments with fuzzy time series

PCL e Silva, CAS Junior, MA Alves, R Silva… - Applied Soft …, 2020‏ - Elsevier
Time series arise in many fields of science such as engineering, economy and agriculture to
cite a few. In the early 1990's the so called Fuzzy Time Series were proposed to handle …

[PDF][PDF] Application of data mining techniques in stock markets: A survey

E Hajizadeh, HD Ardakani… - Journal of …, 2010‏ - mineracaodedados.wordpress.com
One of the most important problems in modern finance is finding efficient ways to summarize
and visualize the stock market data to give individuals or institutions useful information about …

Fuzzy time series forecasting method based on Gustafson–Kessel fuzzy clustering

E Egrioglu, CH Aladag, U Yolcu, VR Uslu… - Expert Systems with …, 2011‏ - Elsevier
Fuzzy time series approaches have being increasingly attracted researchers' attentions. The
procedures on fuzzy time series actually consist of three stages; fuzzification, determination …