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 …

Many fuzzy time series (FTS) methods have been developed by the researchers without
including non-determinacy caused using single function for both membership and non …

One of the main features to invest in stock exchange companies is their financial
performance. On the other hand, conventional evaluation methods such as data …

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 …

Fuzzy inference systems have been commonly used for time series forecasting in the
literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy …

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 …

Fuzzy time series forecasting (FTSF) methods avoid the basic assumptions of traditional time
series forecasting (TSF) methods. The FTSF methods consist of four stages namely …

Fall detection is a critical task in an aging society. To fulfill this task, smart technology
applications have great potential. However, it is not easy to choose a suitable smart …

In this paper, we propose hesitant fuzzy sets-based hybrid time series forecasting method
using particle swarm optimization and support vector machine. Length of unequal intervals …

Fuzzy time series methods, which do not require the strict assumptions of classical time
series methods, generally consist of three stages as fuzzification of crisp time series …