Passenger flow forecast is the prerequisite and foundation for urban rail transit planning and
operation. With the continuous expansion of rail network scale and the surge of passenger …

Provides a unique and methodologically consistent treatment of various areas of fuzzy
modeling and includes the results of mathematical fuzzy logic and linguistics This book is …

This paper is devoted to a method for the forecasting of seasonal time series. The core of our
approach is based on the fuzzy transform and fuzzy natural logic (FNL) techniques. Under …

In this paper, we focus on application of fuzzy transform (F-transform) to analysis of time
series under the assumption that the latter can be additively decomposed into trend-cycle …

Accurate time series forecasting is a key issue to support individual and organizational
decision making. In this paper, we introduce novel methods for multi-step seasonal time …

This paper is devoted to reasoning about fuzzy logic which is based on various personal
observations of the author. Our goal is to think of the state of the art in mathematical fuzzy …

Data clustering is the process of dividing data elements into different clusters in which
elements in one cluster have more similarity than those in other clusters. Semi-supervised …

The aim of this study is to show that the integration of two soft computing techniques, namely
the F-transform and fuzzy tendency modeling, can be successfully used in the analysis and …

The goal of this paper is to provide an overview of applications of special soft computing
theories—the fuzzy transform and fuzzy natural logic—to analysis, forecasting and mining …

The compositions of direct and inverse fuzzy transforms constitute powerful tools in
knowledge extraction and representation that have been applied to a large variety of …