scholarly journals Fuzzy Forecast Based on Fuzzy Time Series

2019 ◽  
Author(s):  
Ming-Tao Chou
Keyword(s):  
Time Series ◽  
Fuzzy Time Series ◽  
Fuzzy Forecast

scholarly journals Fuzzy Time Series Forecasting Model based on Frequency Density and Similarity Measure Approach

2018 ◽  
Vol 7 (4.30) ◽  
pp. 281
Author(s):  
Nazirah Ramli ◽  
Siti Musleha Ab Mutalib ◽  
Daud Mohamad
Keyword(s):  
Time Series ◽  
Similarity Measure ◽  
Fuzzy Numbers ◽  
Historical Data ◽  
Fuzzy Time Series ◽  
Forecasting Model ◽  
Forecasting Accuracy ◽  
Forecasting Error ◽  
Proposed Model ◽  
Fuzzy Forecast

This paper proposes an enhanced fuzzy time series (FTS) prediction model that can keep some information under a various level of confidence throughout the forecasting procedure. The forecasting accuracy is developed based on the similarity between the fuzzified historical data and the fuzzy forecast values. No defuzzification process involves in the proposed method. The frequency density method is used to partition the interval, and the area and height type of similarity measure is utilized to get the forecasting accuracy. The proposed model is applied in a numerical example of the unemployment rate in Malaysia. The results show that on average 96.9% of the forecast values are similar to the historical data. The forecasting error based on the distance of the similarity measure is 0.031. The forecasting accuracy can be obtained directly from the forecast values of trapezoidal fuzzy numbers form without experiencing the defuzzification procedure.

About One Approach to Defuzzifikation of Outputs of Fuzzy Time Series Model

2011 ◽  
Vol 3 (9) ◽  
pp. 562-566
Author(s):  
Ramin Rzayev ◽  
◽  
Musa Agamaliyev ◽  
Nijat Askerov
Keyword(s):  
Time Series ◽  
Time Series Model ◽  
Fuzzy Time Series

Peramalan Data IHSG Menggunakan Metode Backpropagation

2013 ◽  
Vol 5 (1) ◽  
pp. 26-30
Author(s):  
Seng Hansun
Keyword(s):  
Time Series ◽  
Soft Computing ◽  
Fuzzy Time Series

Jaringan saraf tiruan merupakan salah satu metode soft computing yang banyak digunakan dan diterapkan di berbagai disiplin ilmu, termasuk analisis data runtun waktu. Tujuan utama dari analisis data runtun waktu adalah untuk memprediksi data runtun waktu yang dapat digunakan secara luas dalam berbagai data runtun waktu real, termasuk data harga saham. Banyak peneliti yang telah berkontribusi dalam analisis data runtun waktu dengan menggunakan berbagai pendekatan berbeda. Chen dan Hsu, Jilani dkk., Stevenson dan Porter, dan Hansun telah menggunakan metode fuzzy time series untuk meramalkan data mendatang, sementara beberapa peneliti lainnya menggunakan metode hibrid, seperti yang dilakukan oleh Subanar dan Suhartono, Popoola dkk, Popoola, Hansun dan Subanar. Di dalam penelitian ini, penulis mencoba untuk menerapkan metode jaringan saraf tiruan backpropagation pada salah satu indikator perubahan harga saham, yakni IHSG (Indeks Harga Saham Gabungan). Penelitian dilanjutkan dengan menghitung tingkat akurasi dan kehandalan metode yang telah diterapkan pada data IHSG. Pendekatan ini diharapkan dapat menjadi salah satu cara alternatif dalam meramalkan data IHSG sebagai salah satu indikator perubahan harga saham di Indonesia. Kata kunci—jaringan saraf tiruan, backpropagation, analisis data runtun waktu, soft computing, IHSG

A Distributed Algorithm for Scalable Fuzzy Time Series

2019 ◽  
pp. 42-56 ◽  
Author(s):  
Petrônio Cândido de Lima e Silva ◽  
Patrícia de Oliveira e Lucas ◽  
Frederico Gadelha Guimarães
Keyword(s):  
Time Series ◽  
Distributed Algorithm ◽  
Fuzzy Time Series

Fuzzy time series for predicting phenological stages of apple trees

2021 ◽  
Author(s):  
Tiago Boechel ◽  
Lucas Micol Policarpo ◽  
Gabriel de Oliveira Ramos ◽  
Rodrigo da Rosa Righi
Keyword(s):  
Time Series ◽  
Fuzzy Time Series ◽  
Phenological Stages ◽  
Apple Trees

Evolving Fuzzy Time Series for Spatio-temporal Forecasting in Renewable Energy Systems

2021 ◽  
Author(s):  
Carlos A. Severiano ◽  
Petrônio de Cândido de Lima e Silva ◽  
Miri Weiss Cohen ◽  
Frederico Gadelha Guimarães
Keyword(s):  
Time Series ◽  
Renewable Energy ◽  
Energy Systems ◽  
Fuzzy Time Series ◽  
Renewable Energy Systems ◽  
Spatio Temporal

Effective intervals determined by information granules to improve forecasting in fuzzy time series

2013 ◽  
Vol 40 (14) ◽  
pp. 5673-5679 ◽  
Author(s):  
Lizhu Wang ◽  
Xiaodong Liu ◽  
Witold Pedrycz
Keyword(s):  
Time Series ◽  
Fuzzy Time Series ◽  
Information Granules
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