22 Dec 2025Open access
Optimizing irrigation for Dutch roses in Beni Mellal, Morocco: Predictive modeling based on reference evapotranspirationPublisher siteFoods and raw materials, Plant Water Relations and Carbon Dynamics
Active, last published 2026
In smart agriculture and ai
Hamza
Jdi
Scholar“Research focused on Smart Agriculture and AI and adjacent fields.”
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01 · About the work
What I study
amza Jdi is a researcher working on Smart Agriculture and AI. A fuller summary will appear once they update their profile.
02 · Reach
Publication output and reach
Hamza's work has been cited 27 times across 3 active years. Bars show publications per year; the line shows cumulative citation totals across publications first appearing in each year.
03 · Research focus
Topics
Smart Agriculture and AI×4Hydrological Forecasting Using AI×4Energy Load and Power Forecasting×3Hydrology and Drought Analysis×2Greenhouse Technology and Climate Control×2
04 · Where I am
Affiliations
Affiliation on published researchUniversité Sultan Moulay Slimane, MoroccoDrawn from the institution listed on this researcher’s published work.
Research themes (UN SDGs)
05 · Selected work
Recent publications
10 works27 Dec 2024Open access
Hybrid Approaches for Irrigation Optimization Based on Weather Forecast: a Study on Reference Evapotranspiration Prediction in Beni MellalPublisher siteAgris on-line Papers in Economics and Informatics, Hydrology and Drought Analysis
1 Oct 2024Open access1cites
Leveraging transformer models for enhanced temperature forecasting: a comparative analysis in the Beni Mellal regionPublisher siteIndonesian Journal of Electrical Engineering and Computer Science, Energy Load and Power Forecasting
26 Jan 2024Open access4cites
Comparison of time series temperature prediction with auto-regressive integrated moving average and recurrent neural networkPublisher siteInternational Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering, Greenhouse Technology and Climate Control
1 Jan 2024
Temperature Forecast Using Machine LearningPublisher siteLecture notes in networks and systems, Hydrological Forecasting Using AI
28 Jun 2023Open access3cites
The vast relevance of applications of spatial regression models has recently captured the interest of Economics and Agriculture, in the sense of better understanding the spatial behavior of the region under study, in the different forms of approaches. It is interesting to understand why some regions show greater variability than others, and why some forms of regional development are better explained. It is up to the researcher to understand, explore, and organize a series of observations, so that it is possible to make predictions, diagnoses, and recommendations to public policy managers and regional development agents. The municipalities’ Gross Domestic Product (Gdp) has driven studies involving spatial information. The objective of this study was to analyze the Gdp of the municipalities in Paraná-Brazil, in 2018, regarding soybean yield, corn yield, pig production, and the tax on the circulation of goods, through different approaches of spatial regression models. SAR and CAR models are global models, while the GWR model is considered a local one. Three spatial analysis models were used to perform this study: Spatial Autoregressive (SAR), Conditional Autoregressive (CAR), and Geographically Weighted Regression (GWR). The results were compared using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Cross-Validation Criterion (CVC), and the descriptive graphic of residual diagnoses-Worm Plot. The best result obtained was for the GWR model, which best explained the GDP of the state of Paraná-Brazil in terms of its covariates.Publisher siteAgris on-line Papers in Economics and Informatics, Rural Development and Agriculture
27 Jun 2023Open access12cites
Digital Farming: A Survey on IoT-based Cattle Monitoring Systems and DashboardsPublisher siteAgris on-line Papers in Economics and Informatics, Food Supply Chain Traceability
17 May 2023Open access2cites
Precipitation forecasting using machine learning in the region of Beni Mellal-KhenifraPublisher siteIndonesian Journal of Electrical Engineering and Computer Science, Hydrological Forecasting Using AI
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