Prediction of saffron contract yield using the meta-heuristic algorithm

Abstract

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.