Master’s students in Data Science and Big Data at Hassan II University in Casablanca have developed an AI-powered system that ...

A team of Master’s students in Data Science and Big Data at Hassan II University in Casablanca has designed an artificial intelligence-powered system that predicts wildfire risks and offers smart ...

Rahimov, N. and Dilmurod, K. (2015) The Application of Multiple Linear Regression Algorithm and Python for Crop Yield Prediction in Agriculture. Harvard Educational and Scientific Review, 2, 179-187. ...

Making Predictions: Once the logistic regression model is trained and the results are validated, it can predict the probability of a binary outcome for new, unseen data.

Maya Gopal, P.S. and Bhargavi, R. (2019) Performance Evaluation of Best Feature Subsets for Crop Yield Prediction Using ... The optimal feature set returned by different feature selection techniques ...

The project will introduce new technology which can transform how and when farmers water their fields to optimise crop yields, reduce water withdrawals and lower operational costs. The programme is ...

22 You J, Li X, Low M, Lobell D, Ermon S. Deep gaussian process for crop yield prediction based on remote sensing data. InProceedings of the AAAI conference on artificial intelligence 2017;31(1). ...

Assuming a linear connection between crop yield and the input variables such as temperature, rainfall, and fertilizer linear regression is a straightforward and popular approach. A baseline model for ...

Although Logistic function led to statistically significant parameter estimates using NLS approach, as can be seen by a better fit of Richards function than the Logistic function, significant ...

Hence, monitoring an aeroponic crop growth system efficiently is crucial for achieving a high crop yield and reducing the need for food crops. Even though, many crop monitoring systems use IoT and ...