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Bivariate Long Term Fuzzy Time Series Forecasting of Dry Cargo Freight Rates

This paper proposes a bivariate long term fuzzy inference system for time series forecasting task in the field of freight market. Fuzzy time series methods are applied by many scholars and it is broadly accepted pattern recognition and forecasting tool. Previous studies mainly establish algorithms for high frequency time series data such as daily and monthly intervals. The proposed model performs similar techniques for long term annual base data and also extends the conventional method with multi-variate heuristic algorithm. Empirical work is accomplished on shipping freight rate data and life expectancy is used as a leading indicator in the bivariate fuzzy time series model.

Ketersediaan
#
IPC Corporate University Library ATC LO DUR b C.1
ATC1802822
Tersedia
Informasi Detail
Judul Seri
The Assian Journal of Shipping and Logistics
No. Panggil
ATC LO DUR b C.1
Penerbit
TUREY : .,
Deskripsi Fisik
205 p.
Bahasa
English
ISBN/ISSN
-
Klasifikasi
LO
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
online resource
Edisi
Volume 26 Number 2 December 2010 pp. 205-223
Subjek
Forecasting
Fuzzy Time Series
Multi-variate Modelling
Freight Rate
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Versi lain/terkait
Lampiran Berkas
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