The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …

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 …

Given the high potential benefits and impacts of accurate stock market predictions,
considerable research attention has been devoted to time series forecasting for stock …

Time series analysis and forecasting future values has been a major research focus since
years ago. Time series analysis and forecasting in time series data finds it significance in …

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 …

Over the last three decades, several researchers have been putting their efforts into
develo** non-deterministic fuzzy time series (FTS) models using the traditional fuzzy set …

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 …

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 …

In the fashion retail industry, level of forecasting accuracy plays a crucial role in retailers'
profit. In order to avoid stock-out and maintain a high inventory fill rate, fashion retailers …