Ansari ghojghar, M. (2023). Development of strategic wheat crop prediction toolkit using machine learning algorithms to reduce food security risks (case study: alborz province), Iranian Journal of Soil and Water Research, 53(10), 2277-2294. [In Persian]. doi: 10.22059/ijswr.2022.342638.669260.
Bazgeer, S. & Kamali, GH.A. (2008). Wheat yield prediction using agro meteorological indices For some regions of the Western of the country, Journal of Agricultural Sciences and Natural Resources, 15(2), 113, 121. [In Persian]. DOI: 10.22059/jdesert.2008.31063
Bazgeer, S., Kamali, G. & Mortazavi, A. (2007). Wheat yield prediction through agrometeo-rological indices for Hamedan, Iran, Biaban (Desert Journal), 12, 33-38. doi: 10.22059/jdesert.2008.31063.
Biswas, T., Majumder, A., Dey, S., Mandal, A., Ray, S., Kapoor, P., Emam, W., Kanthal, S., Ishizaka, A. & Matuka A. (2021). Evaluation of management practices in rice–wheat cropping system using multicriteria decision-making methods in conservation agriculture, Scientifc Reports, 13, 14(1), 8600. doi: 10.1038/s41598-024-58022-w.
De Brito, M. M. & Evers, M. (2016). Multi-criteria decision-making for flood risk management: a survey of the current state of the art, Natural Hazards and Earth System Sciences, 16(4), 1019-1033. doi: 10.5194/nhess-16-1019-2016.
Dehghani Sargazi, H., Bazrafshan, O. & Zamani, H. (2021). Investigation of the effect of meteorological-agricultural drought on rainfed wheat yield in Iran using SPEI, Nivar, 45(114), 16-28. [In Persian]. doi: 10.30467/nivar.2021.295544.1198.
Delghandi, M., Joorablou, S. & Ganji Nowroozi, Z. (2023). The impact of climate change on severity, duration, and magnitude of drought using SPI and RDI in the Semnan region, Journal of Drought and Climate change Research, 1(1), 1-18. [In Persian]. doi:10.22077/jdcr.2023.5909.1004.
Farajzadeh, M. & Khorani, A., Bazgir, S. & Zeaiean, P. (2013). Estimation of rainfed wheat yield using climatic-agricultural indicators and remote sensing in Kurdistan province, Iranian Remote Sensing and GIS Journal, 5(2), 35-52. [In Persian].
Khadempour, F., Khashei Siuki, A. & Behdani, M. A. (2020). Evaluation of the efciency of Lazy Algorithm in Estimating Yield of Saffron Based on Climatic Parameters, Saffron Agronomy and Technology, 8(2), 295-304. doi: 10.22048/jsat.2020.174803.1338
Khodjaev, S., Kuhn, L., Bobojonov, I. & Glauben, T. (2024). Combining multiple UAVBased indicators for wheat yield estimation, a case study from Germany, European Journal of Remote Sensing, 57(1), 2294121. doi: 10.1080/22797254.2023.2294121.
Khosravirad, M., Omid, M., Sarmadian, F. & Hosseinpor, S. (2019). Sugarcane yield estimation using LANDSAT time series imagery (Case Study-MianAB region in Khouzestan Province), Iranian Journal of Biosystem Engineering, 50 (2), 399-414. [In Persian]. doi: 10.22059/IJBSE.2019.268449.665108.
Madani, A., Khasheyi, A., & Khakzad, S. (2021). Predictingrain fed barley crop yield using artifcial neural network and fuzzy neural systems in Khorasan province –Iran, Journal of Plant Production, 11(2), 75-92. [In Persian]. doi: 10.2./ jpps.2022.691244.
Mathieu, J. A., & Aires, F. (2018). Assessment of the agro-climatic indices to improve crop yield forecasting, Agricultural and forest meteorology, 253, 15-30. doi: 10.1016/j.agrformet.2018.01.031.
Niedbała, G., Nowakowski, K., Rudowicz-Nawrocka, J., Piekutowska, M., Weres, J., Tomczak, R.J., Tyksiński, T. & Álvarez Pinto, A. (2019). Multicriteria prediction and simulation of winter wheat yield using extended qualitative and quantitative data based on artifcial neural networks, Applied Sciences, 9(14), 2773. doi: 10.3390/app9142773.
Parviz, L. & Bonyadi, H. 2019. Wheat yield modeling using climate indices and hierarchical, Ecohydrology, 6(2), 479-491. [In Persian]. doi: 10.22059/ije.2019.272286.1013.
Parviz, L.& Paymai. M. (2019). Stochastic climatological yield forecasting of four crops wheat, barley, potato and maize in East and West Azer-baijan Provinces in the development of agricultural planning, Crop production, 11(4), 11-26. [In Persian]. doi: 10.22069/ejcp.2019.14153.2077.
Seyed Jalali, S.A., Sarmadian, F., Shorafa, M. & Mohammad Ismail, Z. (2016). Application of kriging and cokriging in predicting wheat yield using principal component analysis, Crop production Journal, 9(2), 213-224. [In Persian]. doi: 10.22069/ejcp.2016.3124.
Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., Ghorbani, M. A. & Shahbazi, F. (2018). Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops, Geoderma, 310, 178-190. doi: 10.1016/j.geoderma.2017.09.012.
Tanabe, R., Matsui, T. & Tanaka, T.S. (2023). Winter wheat yield prediction using convolution neural networks and UAV-based multispectral imagery, Field Crops Research, 291, 1087. doi: 10.1016/j. fcr.2022.108786.
Wang, H., Wang, X., Bi, L., Wang, Y., Fan, J., Zhang, F. & Xiang, Y. (2019). Multi-objective optimization of water and fertilizer management for potato production in sandy areas of northern China based on TOPSIS, Field Crops Research, 240, 55-68. doi: 10.1016/j.fcr.2019.06.005.