AKINER, M. E. And Ghasri, M. 2024. Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration. Environmental Science and Pollution Research , vol.31, no.30 , 42719-42749.

AKINER, M. E., & Ghasri, M., (2024). Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration. Environmental Science and Pollution Research , vol.31, no.30, 42719-42749.

AKINER, MUHAMMED, And Mehdi Ghasri. "Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration," Environmental Science and Pollution Research , vol.31, no.30, 42719-42749, 2024

AKINER, MUHAMMED E. And Ghasri, Mehdi. "Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration." Environmental Science and Pollution Research , vol.31, no.30, pp.42719-42749, 2024

AKINER, M. E. And Ghasri, M. (2024) . "Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration." Environmental Science and Pollution Research , vol.31, no.30, pp.42719-42749.

@article{article, author={MUHAMMED ERNUR AKINER And author={Mehdi Ghasri}, title={Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration}, journal={Environmental Science and Pollution Research}, year=2024, pages={42719-42749} }