series neural network with bootstrap model, is composed of a dynamic n-order 2-factor fuzzy time series model, a radial basis … function neural network model and a bootstrap method. In the proposed model, the dynamic n-order 2-factor fuzzy time series … hybrid model to forecast the option price. The proposed model, termed as the dynamic weighted distance-based fuzzy time …

index combined with the establishment of fuzzy time series models can be used to predict future trends in the trading range … of the global steel price index. Analysis of applied fuzzy time series data shows the following results: (1) Price …

Fuzzy time-series models have been utilized in making reasonably accurate predictions in many areas, such as academic … enrollments, weather forecasting and stock markets. To refine past fuzzy time-series models, this paper proposes a new model … comparison results show that the proposed model surpasses in accuracy one traditional fuzzy time-series model and two advanced …

Fuzzy time series forecasting methods do not require constraints found in conventional approaches. In addition, due to … uncertainty that they contain, many time series to be forecasted should be considered as fuzzy time series. Fuzzy time series … the time series encountered in real life contain seasonal component, only few of these fuzzy time series approaches …

underperform on a data set that exhibit uneven ups and downs (turbulences). In this paper, a new method based on fuzzy time-series … based fuzzy time series forecasting is effective, especially, when the available data indicate a high degree of instability …

In recent years, various methods for forecasting fuzzy time series have been presented in different areas, such as …

Purpose – Many studies have proposed variant fuzzy time series models for uncertain and vague data. The purpose of this … paper is to adapt a fuzzy time series combined with genetic algorithm (GA) to forecast tourist arrivals in Taiwan. Design …/methodology/approach – Different cases are studied to understand the effect of variation of fuzzy time series order, number of intervals and population …