Effect of Fuzzy Time Series Technique on Estimators of Spectral Analysis

Authors

  • Abd El-Moneim A. M. Teamah Mathematics Department, Faculty of Science, Tanta University, Tanta, Egypt.
  • Hasnaa M. Faied Mathematics Department, Faculty of Science, A1-Azhar University (Girls), Nasr-City, Cairo, Egypt.
  • Mohammed H. El-Menshawy Mathematics Department, Faculty of Science, A1-Azhar University (Men), Nasr-City, Cairo, Egypt.

DOI:

https://doi.org/10.9734/bpi/ramrcs/v6/1506B

Keywords:

Time series, Fuzzy time series, Fuzzy sets, Fuzzy logical relationships, Fuzzy observations, Spectral density function, Periodogram, Estimation

Abstract

In this chapter, we study the estimation of the spectral density function as well as the properties of the resulting estimator, known as the periodogram. The statistical properties of this periodogram for actual and forecasted observations of the fuzzy time series are investigated. The periodogram results in both cases can be compared based on MSEs, which are based on these statistical properties. A programme that converts observed time series to fuzzy time series with large sizes is created for this purpose.

Study Objective: Using the fuzzy time series technique to improve the estimation of the spectral density function while retaining its statistical properties.  

Published

2022-01-01

How to Cite

Abd El-Moneim A. M. Teamah, Hasnaa M. Faied, & Mohammed H. El-Menshawy. (2022). Effect of Fuzzy Time Series Technique on Estimators of Spectral Analysis. Recent Advances in Mathematical Research and Computer Science Vol. 6, 29–38. https://doi.org/10.9734/bpi/ramrcs/v6/1506B

Issue

Recent Advances in Mathematical Research and Computer Science Vol. 6

Section

Chapters