Authors - Sanae.Chakir, Adil.Bekraoui, El moukhtar Zemmouri, Hassan.Majdoubi, Mhamed. Mouqallid Abstract - For cuttings to successfully root indoor environmental conditions in a greenhouse are essential. This article examines the efficacy of two predictive models, linear regression and artificial neural networks, in predicting the parameters associated with rooting plant cuttings. For evaluation the analysis uses the RMSE MAPE and R² indices. According to the results artificial neural networks perform better than linear regression in terms of prediction accuracy. By utilizing these insights, farmers can use artificial neural network models to implement optimal control strategies which will al-low them to accurately predict indoor variables and ultimately increase crop productivity.
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