Better forecasting energy demand in China and India can help those countries meet future
challenges caused by the changes in that demand, as well as inform future global energy …

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 study, we develop an approach to multivariate time series anomaly detection focused
on the transformation of multivariate time series to univariate time series. Several …

In this paper, we propose a new multiple attribute decision making (MADM) method based
on the nonlinear programming (NLP) methodology, the TOPSIS method and interval-valued …

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 …

Multi-attribute decision-making (MADM) can be regarded as a process of selecting the
optimal one from all objects. Traditional MADM problems with intuitionistic fuzzy (IF) …

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 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 …

With atmospheric environmental pollution becoming increasingly serious, develo** an
early warning system for air quality forecasting is vital to monitoring and controlling air …

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 …