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 ۲۰۱۸ to ۲۰۲۱ was ۵ 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.

کلیدواژه ها:

Saffron Binding Efficiencies ، metaheuristic algorithm ، Bird Algorithm ، BAT Algorithm ، Cuckoo algorithm