Prediction of saffron contract yield using the meta-heuristic algorithm

Document Type : Research Paper


Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran


The main purpose of this study is to predict saffron’s binding efficiency using the meta-heuristic algorithm. This collection of information is a documentary research library and the result is quantitative research. The time period from 2018 to 2021 was 5 years and the frequency of daily frequencies of the Ministry of Agricultural Jihad and Customs of Iran were collected from the Iran Mercantile Exchange (JPI). The meta-heuristic algorithm consisting of a combination of birds, bats, and cuckoos was designed. The proposed methods were modelled by coding in a MATLAB environment using normal data. The results of the computational analysis show that all models were approved; And the artificial neural network shows that price fluctuations, cash price, the volume of transactions and liquidity are of the most importance, respectively, on the yield of saffron contracts.


Articles in Press, Corrected Proof
Available Online from 24 December 2022
  • Receive Date: 13 September 2022
  • Revise Date: 23 October 2022
  • Accept Date: 15 December 2022
  • First Publish Date: 24 December 2022