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 …

In this paper, we propose a new fuzzy time series forecasting method for forecasting the
Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time …

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 …

In this paper, we propose a new fuzzy time series (FTS) forecasting method based on
optimal partitions of intervals in the universe of discourse and optimal weighting vectors of …

Rising market demands, economic pressures, and technological advancements have
spurred researchers to seek ways to enhance business environments and scientific …

In this paper, we propose a new fuzzy time series (FTS) forecasting method based on the
proportions of intervals and particle swarm optimization (PSO) techniques. First, it uses PSO …

The study shows that there are two main problems that affect the performance of fuzzy time
series (FTS) models, namely the selection of the universe of discourse and the …

Time series analysis is a method to predict future values based on previously observed
values. Assuming the observed values are imprecise and described by uncertain variables …

In this paper, we propose a new fuzzy forecasting method based on two-factors second-
order fuzzy-trend logical relationship groups (TSFTLRGs), particle swarm optimization (PSO) …

In this paper, a new method for forecasting the TAIEX is presented based on fuzzy time
series, particle swarm optimization techniques and support vector machines. The proposed …