Forecasting data is still an extensively investigated area of research specially in stock
markets. The subjectivity of the elements that influence the market oscillation is the main …

Forecasting data is still an extensively investigated area of research specially in stock
markets. The subjectivity of the elements that influence the market oscillation is the main …

After reviewing the vast body of literature on using FTS in stock market forecasting, certain
deficiencies are distinguished in the hybridization of findings. In addition, the lack of …

Recently, many fuzzy time series models have already been used to solve nonlinear and
complexity issues. However, first-order fuzzy time series models have proven to be …

Fuzzy forecasting approaches are mainly based on the modeling of fuzzy logical
relationships of the historical data. In this paper, an improved model for forecasting stock …

In this study, a new kind of fuzzy set in fuzzy time series' field is introduced. It works as a
trend estimator to be appropriate for fuzzy time series forecasting by reconnoitering trend of …

This paper presents a new fuzzy time series model combined with ant colony optimization
(ACO) and auto-regression. The ACO is adopted to obtain a suitable partition of the universe …

In real time, one observation always relies on several observations. To improve the
forecasting accuracy, all these observations can be incorporated in forecasting models …

In recent years, there are several ongoing efforts to develop models for forecasting fuzzy
time series using classical or artificial intelligence (AI) techniques in different application …

Since people cannot predict accurately what will happen in the next moment, forecasting
what will occur mostly has been one challenging and concerned issues in many areas …