We propose a fuzzy time series forecasting method using hesitant fuzzy sets.An aggregation operator is also proposed to aggregate hesitant fuzzy elements.Hesitancy is introduced by using multiple fuzz...
Uncertainties due to randomness and fuzziness coexist in the system simultaneously. Recently probabilistic fuzzy set has gained attention of researchers to handle both types of uncertainties simultane...
Time series have attracted widespread attention in many fields today. Based on the analysis of complex networks and visibility graph theory, a new time series forecasting method is proposed. In time s...
Time series forecasting models based on a linear relationship model show great performance. However, these models cannot handle the the data that are incomplete, imprecise, and ambiguous as the interv...
This study presents a new method of forecasting based on a higher order intuitionistic fuzzy time series (FTS) by transforming FTS data into intuitionistic FTS data via defining their appropriate m......
This research introduces a neutrosophic forecasting approach based on neutrosophic time series (NTS). Historical data can be transformed into neutrosophic time series data to determine their truth, in...
This paper proposes a semiparametric autoregressive integrated moving average model for those real-world applications whose observed data are reported by fuzzy numbers. To this end, a hybrid method in...
This paper proposed a novel first-order single-valued neutrosophic hesitant fuzzy time series (SVNHFTS) forecasting model. Our aim is to improve the previously proposed neutrosophic time series (NTS) ...
This paper considers a class of bi-matrix games involving two players with their payoffs matrices having entries from the set of trapezoidal intuitionistic fuzzy numbers. We generalize the notion of N...
This article provides new application-independent perspectives about the performance potential of an intuitionistic (I-) fuzzy system over a (classical) Takagi–Sugeno–Kang (TSK) fuzzy system. It does ...
The time series analysis is mainly aimed at establishing a fuzzy prediction model based on a set of real-valued time series data. To achieve this goal, the present paper proposes a different strategy ...
The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) p...
The Internet performance directly affects the scalability, reliability and availability of the online applications. Delay of a few millisecond may cause companies lose millions of dollars. Therefore, ...
Recently, the probabilistic fuzzy set has been applied by the researchers in various domains to model the uncertainties in the system due to both fuzziness and randomness. In this research paper, we p...
Recently time series prediction based on network analysis has become a hot research topic. However, how to more accurately forecast time series with good efficiency is still an open question. To addre...
Over the years, numerous fuzzy time-series forecasting (FTSF) models have been developed to handle the uncertainty and non-determinism in the time-series (TS) data. To handle the non-determinism and i...
Non-stochastic hesitation in fuzzy time series forecasting methods occurs due to availability of more than one fuzzification methods of time series data. Recently hesitant fuzzy set has gained attenti...
Intuitionistic fuzzy sets are extended form of type 1 fuzzy sets. The modeling methods use intuitionistic fuzzy sets have second-order uncertainty approximation so these methods may have better result...
Intuitionistic fuzzy set plays a vital role in data analysis and decision-making problems. In this paper, we propose an enhanced and versatile method of forecasting using the concept of intuitionistic...
In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between ne...