prediction of saffron contract yield using the meta-heuristic algorithm

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.