Wind speed forecasting is gaining importance as the share of wind energy in electricity
systems increases. Numerous forecasting approaches have been used to predict wind …

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 …

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 …

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 …

Time series forecasting has been widely used to determine future prices of stocks, and the
analysis and modeling of finance time series is an important task for guiding investors' …

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) …

Financial time series prediction problems, for decision-makers, are always crucial as they
have a wide range of applications in the public and private sectors. This study presents a …

Accurate wind speed forecasting is crucial for wind energy development and utilization. The
non-linearity and non-stationarity of the wind speed leads to difficulties in its prediction …

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 …

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 …