Journal of Sensor Networks and Data Communications(JSNDC)

Department of Computer Science, University Joseph KIZERBO (U-JKZ), Ouagadougou, Burkina Faso

Publications

• Research Article   
  A Robust Crop Recommendation System Leveraging Soil and Climate Parameters
  Author(s): Desire Guel* and Jimna Kongo*
  
  We present a benchmarking study of classical machine learning (ML) methods for crop recommendation from soil and climate parameters with an emphasis on methodological transparency, interpretability and deployability in low-resource contexts. We evaluate K-Nearest Neighbors (KNN), Random Forest (RF), Sup- port Vector Classifier (SVC), Gaussian Na Ì?ıve Bayes (NB), Bagging (BG) and a soft-voting ensemble, trained and validated on a curated dataset of N =2,200 instances comprising N–P–K, pH, rainfall, humidity and temperature features [1]. Models are tuned via nested, stratified k-fold cross-validation and assessed using accuracy, precision, recall and F1-score with 95% confidence intervals (bootstrap). Beyond aggregate metrics, we report global permutation importance and partial dependence to enhance interpretability; we further discuss temporal extensions (e.g., LSTM) for .. Read More»
  

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