In this paper, we have proposed a new modified forecasting method based on time-variant fuzzy time series. It uses trend heuristics in addition to high-order fuzzy logical relations and enhances the average forecasting accuracy significantly. To illustrate the whole forecasting process, we use actual enrollments (historical data for 22 years) of the University of Alabama (UA) and compare results obtained through other well-known fuzzy time seriesbased approaches described up to date in the literature. As a result, for all examined cases, the new time-variant method yields better forecasting accuracy as compared with alternative methods
Most fuzzy forecasting approaches are based on model fuzzy logical relationships according to the pa...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...
In recent years, time series forecasting studies in which fuzzy time series approach is utilized hav...
The Time-Series models have been used to make predictions in whether forecasting, academic enrollmen...
In this paper we propose a new method to forecast enrollments based on fuzzy time series. The propos...
This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy ...
In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time ser...
[[abstract]]Traditional time series methods fail to forecast the problems with linguistic historical...
The Time-Series models have been used to make predictions in whether forecasting, academic enrollmen...
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, an...
Many forecasting models based on the concepts of fuzzy time series have been proposed in the past de...
Abstract. During the last decade different time series models have been designed and developed. The ...
Abstract—A number of forecasting models have been proposed based on fuzzy time series in the past 20...
Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and...
AbstractThe fuzzy time series has recently received increasing attention because of its capability o...
Most fuzzy forecasting approaches are based on model fuzzy logical relationships according to the pa...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...
In recent years, time series forecasting studies in which fuzzy time series approach is utilized hav...
The Time-Series models have been used to make predictions in whether forecasting, academic enrollmen...
In this paper we propose a new method to forecast enrollments based on fuzzy time series. The propos...
This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy ...
In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time ser...
[[abstract]]Traditional time series methods fail to forecast the problems with linguistic historical...
The Time-Series models have been used to make predictions in whether forecasting, academic enrollmen...
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, an...
Many forecasting models based on the concepts of fuzzy time series have been proposed in the past de...
Abstract. During the last decade different time series models have been designed and developed. The ...
Abstract—A number of forecasting models have been proposed based on fuzzy time series in the past 20...
Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and...
AbstractThe fuzzy time series has recently received increasing attention because of its capability o...
Most fuzzy forecasting approaches are based on model fuzzy logical relationships according to the pa...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...
In recent years, time series forecasting studies in which fuzzy time series approach is utilized hav...