A hybrid time series forecasting method based on neutrosophic logic with applications in financial issues

Author:

Edalatpanah Seyyed AhmadORCID,Hassani Farnaz Sheikh,Smarandache Florentin,Sorourkhah AliORCID,Pamucar DraganORCID,Cui Bing

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference79 articles.

1. Improving demand forecasting with LSTM by taking into account the seasonality of data;Abbasimehr;Journal of Applied Research on Industrial Engineering,2020

2. A comparative study of demand forecasting based on machine learning methods with time series approach;Abbaspour Ghadim Bonab;Journal of Applied Research on Industrial Engineering,2022

3. A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty;Abdi;Int. J. Syst. Sci.: Operations and Logistics,2021

4. Forecasting of COVID-19 sixth peak in Iran based on singular spectrum analysis;Abdolhosseini;Journal of Decisions and Operations Research,2023

5. On the Introduction to neutrosophic statistics and neutrosophic algebraic structures (involving the fuzziness, similarity and the symmetry properties on the neutrosophic interval probability) (1);Adebisi;Journal of Fuzzy Extension and Applications,2022

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