پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شمارهها | 702 |
| تعداد مقالات | 10,100 |
| تعداد مشاهده مقاله | 71,347,468 |
| تعداد دریافت فایل اصل مقاله | 63,061,239 |
Prediction of saffron contract yield using the meta-heuristic algorithm | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 17، دوره 14، شماره 9، آذر 2023، صفحه 251-262 اصل مقاله (1.68 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.7250 | ||
| نویسندگان | ||
| Mahvash Farrokhi؛ Ali Najafi Moghadam* ؛ Roya Darabi | ||
| Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| تاریخ دریافت: 22 شهریور 1401، تاریخ بازنگری: 01 آبان 1401، تاریخ پذیرش: 24 آذر 1401 | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Saffron Binding Efficiencies؛ Metaheuristic Algorithm؛ Bird Algorithm؛ Bat Algorithm؛ Cuckoo Algorithm | ||
| مراجع | ||
|
[1] P. Adam, U. Rianse, L.M. Harafah, E. Cahyono and M. Rafiy, A model of the dynamics of the effect of world crude oil price and world rice price on Indonesia’s inflation rate, Agris On-Line Papers Econ. Inf. 8 (2016), no. 665-2016-45110, 3–12. [2] A.M. Ahmadvand and F. Javadi Rizi, Presenting a model for predicting the price of gold coins in Iran using neural networks, genetic phase algorithm, Master’s Thesis, Faculty of Electricity, Computer and Mechanics, 2018. [3] A.R. Amerian, E. Chirani and M.H. Gholizade, Financial crimes; Model design and explanation by grounded theory method, Invest. Sci. Res. Quart. 10 (2021), no. 38, 265–285. [4] D. Bredin, C. O’Sullivan and S. Spencer, Forecasting WTI crude oil futures returns: Does the term structure help?, Energy Econ. 100 (2021), 105350. [5] R. Durgut and M.E. Aydin, Adaptive binary artificial bee colony algorithm, App. Soft Comput. 101 (2021), 107054. [6] H. Liu, Y. Liu and Y. Wang, Exploring the influence of economic policy uncertainty on the relationship between tourism and economic growth with an MF-VAR model, Tourism Econ. 27 (2021), no. 5, 1081–1100. [7] Y. Mehri, M. Mehri and J. Soltani, Evaluation of integrated models using meta-heuristic algorithms of bird optimization and genetics in ANFIS model to predict pollutant emission coefficient in rivers, Water Irrig. Manag. 10 (2019), no. 1. [8] W. Metzner, Echolocation behaviour in bats, Sci. Prog. 75 (1991), no. 3/4, 453–465. [9] H. Mirqaderi and M. Zandiyeh, Design of a new meta-heuristic algorithm based on the behavior of mathematical functions xCos(x) and tanh(x), J. Ind. Manag. Persp. 1 (2011), no. 2, 107–123. [10] J. Qasemi and S. Farzad, An overeview of the algorithm of meta-heuristic algorithms in financial field, Comerc. Surv. 17 (2018), no. 96, 56–77. [11] A. Sadeghieh and S. Feridouni, Metaheuristic methods (introduction of cuckoo optimization algorithm), Yazd University, 2012. [12] A. UJI, Investigating the causal structure of daily corn contracts in producing countries in the midwestern United States, Qual. Rep. 2 (2017), no. 4, 1–15. [13] X.-S. Yang, A new metaheuristic bat-inspired algorithm, Nature inspired cooperative strategies for optimization (NICSO 2010), Springer, Berlin, Heidelberg, 2010, pp. 65–74. [14] H. Zhao, Z.G. Chen, Z.H. Zhan, S. Kwong and J. Zhang, Multiple populations co-evolutionary particle swarm optimization for multi-objective cardinality constrained portfolio optimization problem, Neurocomput. 430 (2021), 58–70. | ||
|
آمار تعداد مشاهده مقاله: 17,019 تعداد دریافت فایل اصل مقاله: 10,581 |
||